Pith. sign in

Paper Citation Record · LEDGER

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images

As of 18 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2501.00360.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.00360 v1

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:56:50.799882Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

72 of 72 outbound references displayed

  • verified exact1
  • verified fuzzy60
  • unresolved10
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation df8ec648-bb71-420a-bc68-1e04f0096594 · outbound

This paper cites an unresolved cited work.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:56:51.796941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.499288Z digest=sha256:6c60d20d5ef6c8e3d6ef4ef901a9ced66ef797982a036f5f7dd0eb276157c983

Observation 671420db-a578-45f4-8815-a781dee8d719 · outbound

This paper cites an unresolved cited work.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:56:51.783638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.503757Z digest=sha256:ed70c2ea5ec71ca23e49ee91d6605646ce7a8fb13f307a96b48c4aedaff0bae1

Observation a8d02479-5c02-480e-afa5-8efa9f21779c · outbound

This paper cites The NWPU VHR-10 dataset contains 650 remote sensing images and corresponding instance annotations collected from Google Earth and ISPRS Vaihingen datasets [28].

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images The NWPU VHR-10 dataset contains 650 remote sensing images and corresponding instance annotations collected from Google Earth and ISPRS Vaihingen datasets [28]

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.730263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.523002Z digest=sha256:7950ee974662678d307e6678c49e81361373f4eab05dbd0a5c17e7deda639354

Observation a14c0409-9e7a-442c-8d6f-508b1ac58bcb · outbound

This paper cites W, H and C.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images W, H and C

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.770050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.508724Z digest=sha256:40c900896d1267ae71d938d4b6261edf4336fef93dcb61dc2e5d97057e581ffe

Observation 81423554-64fc-4517-a1b2-ef67fa2d4234 · outbound

This paper cites an unresolved cited work.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:56:51.756245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.513531Z digest=sha256:6609f65b91ee49e9a49e2d198ec0988da78e37a4db4f20f0e5e007f6d3ca1bae

Observation 131bacb3-0309-4706-b06a-b6378793b223 · outbound

This paper cites an unresolved cited work.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:56:51.743159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.518102Z digest=sha256:7c89d6d553711dd6b4255182581a845ff880691dbc514f090d991b98cd9fbb92

Observation 62b049ed-7f28-4f23-97ec-d773e5fbb0ca · outbound

This paper cites Multi-Swin Mask Transformer for Instance Segmentation of Agricultural Field Extraction,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Multi-Swin Mask Transformer for Instance Segmentation of Agricultural Field Extraction,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.524635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.587887Z digest=sha256:e859a73cb7f5edc995bf7280e514956e359bb8bb77bbc0b3ac33fc9d5c7e8c8d

Observation 992d5dc7-5030-4d50-a409-74b669124244 · outbound

This paper cites an unresolved cited work.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:56:51.716484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.527217Z digest=sha256:5ebab70075d5a1607a406937d4ed1d9098f12318892b5d673ca130aec2c8d51b

Observation 6f02c95a-f438-4353-91a3-a1aad7fd75e0 · outbound

This paper cites an unresolved cited work.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:56:51.810598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.493974Z digest=sha256:4d0e90d38a086e8f4ce2526deaa30fb260c48da65263ec9b1b9c5e71bb169722

Observation 30843a2a-e279-491e-9874-e4f49a2d083b · outbound

This paper cites an unresolved cited work.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-10T22:56:51.701676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.531585Z digest=sha256:dc3a35db2d540fed6c2dcf83a3df8fd79d9bcedac838c68765293dc5bf933d84

Observation f81ecf53-235c-4dac-aa60-4aae8686208f · outbound

This paper cites The quantitative results of the proposed SGTN and other comparison methods are listed in Table I.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images The quantitative results of the proposed SGTN and other comparison methods are listed in Table I

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.687349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.535741Z digest=sha256:464c655282c52ebf1e3baefe3d4b29857d00d2376605156ed4028ecdf14ff475

Observation eac123f4-78e9-463d-8bdc-68e78ad74293 · outbound

This paper cites The quantitative results from different instance segmentation methods on the BITCC dataset are listed in Table II.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images The quantitative results from different instance segmentation methods on the BITCC dataset are listed in Table II

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.674225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.539892Z digest=sha256:733b99f475b53caaf1aa7db037428ac8899cf0f12eb08fe3d5b33a9b77f882f4

Observation 240da120-1c5b-4e9a-8d1e-7126e2626b74 · outbound

This paper cites Results on the multi-category NWPU VHR-10 dataset from different instance segmentation methods are summarized in Table III.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Results on the multi-category NWPU VHR-10 dataset from different instance segmentation methods are summarized in Table III

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.660701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.544585Z digest=sha256:07ffb889438912ebcf49de05b18ce133d5dfc2d62bed60ef0e7bc11a40f8d705

Observation 07c7dcda-1121-4942-b704-13653d869b58 · outbound

This paper cites In this subsection, we analyze the inference efficiency of our newly developed method for instance segmentation of remote sensing images.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images In this subsection, we analyze the inference efficiency of our newly developed method for instance segmentation of remote sensing images

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.633975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.553304Z digest=sha256:33d067504a09de6381a4779c26f1e2e2afac3e5f9a6c185aad21440065122b31

Observation 03773622-30c0-49f2-9677-3a715fa9f832 · outbound

This paper cites W/” DENOTES WITH, “W/O.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images W/” DENOTES WITH, “W/O

Reference 15

Resolution
malformed identifier
raw_fallback, observed 2026-08-10T22:56:51.620552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.557394Z digest=sha256:270523c675122ae49addaae0180449224d934aed2e7c436c96903ad723cd5ad3

Observation 1d297da5-46b3-45a6-87b0-aaa88fd0c0ea · outbound

This paper cites Mask Decoupled Head for Instance Segmentation in Remote Sensing Images.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Mask Decoupled Head for Instance Segmentation in Remote Sensing Images

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.606741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.561746Z digest=sha256:ea7647116ea0a372e8acb6158cb75932dbbc0b8853dd707a6d74e8e96d62f8c1

Observation 7bd0eceb-248c-4292-81c0-f7696748e214 · outbound

This paper cites Instance Segmentation in Very High Resolution Remote Sensing Imag ery Based on Hard-to-Segment Instance Learning and Boundary Shape Analysis,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Instance Segmentation in Very High Resolution Remote Sensing Imag ery Based on Hard-to-Segment Instance Learning and Boundary Shape Analysis,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.593409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.566110Z digest=sha256:ca340602c8549261befa88f511ebf5400e85cb47280a5b247dc0c0f67641a5c0

Observation 75bb1b9a-7e22-482b-8dcf-f1b75fafac19 · outbound

This paper cites Accurate Instance Segmentation for Remote Sensing Images via Adaptive and Dynamic Feature Learning,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Accurate Instance Segmentation for Remote Sensing Images via Adaptive and Dynamic Feature Learning,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.579617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.570321Z digest=sha256:55ccc84b947e509ab3314505d8ec1b09e35311a91872e2cd724cf731952bdd26

Observation 37d2ea40-1a75-4483-97d9-352af82eb544 · outbound

This paper cites Simultaneous detection and segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Simultaneous detection and segmentation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.565860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.574647Z digest=sha256:d3820f85ba8a339bf4edf010274f5483c96d6d048b5f5c96c52922261070c5b2

Observation dfe90dc6-743f-481e-bfb5-5446f16cd0ed · outbound

This paper cites An anchor-free network with box refinement and saliency supplement for instance segmentation in remote sensing images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images An anchor-free network with box refinement and saliency supplement for instance segmentation in remote sensing images,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.552183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.579430Z digest=sha256:cf9299530fb84fa806513627cd116875f3f2338e402867578af7ae2898a722b4

Observation 7cb5d188-157a-4a10-aeec-30d59a74925f · outbound

This paper cites Bounding box-free instance segmentation using semi-supervised iterative learning for vehicle detection.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Bounding box-free instance segmentation using semi-supervised iterative learning for vehicle detection

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.539026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.583764Z digest=sha256:55bb56c09050dc73dee9ea0cd61af44a6c7eb3db29c08f5051f2c4085629ec51

Observation 92e237df-b94f-42c1-aeb2-711b438740f3 · outbound

This paper cites Polarmask: Single shot instance segmentation with pola r representation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Polarmask: Single shot instance segmentation with pola r representation

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.335904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.650809Z digest=sha256:461b102bd4186b09567e90529819e0367651cacd60f3bf036ad1a1dcf089faa8

Observation c922b180-435b-4373-8379-8fe9de53e159 · outbound

This paper cites Long-Range Correlation Supervision for Land-Cover Classification from Remote Sensing Images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Long-Range Correlation Supervision for Land-Cover Classification from Remote Sensing Images,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.511952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.592020Z digest=sha256:e1cf38dbfaac9e6eab0f661a5d8bebf2940770cd33e1837b7a0b846695d3bf85

Observation 3163aacb-620a-487e-bad4-7b0990f13883 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.498882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.596290Z digest=sha256:66cad57c520b0c33bd26a2e21bf15972ff80b315cc8a52d880e99bbd2382b956

Observation 92653dad-6b96-4169-87e6-bd64074e7e13 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Swin transformer: Hierarchical vision transformer using shifted windows

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.486254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.600376Z digest=sha256:7898e7a24ebe98809b834e2882fab79287af2eeadf6cef1b71f798b16ca89978

Observation c1e191b3-474c-4f29-938f-918d46921c35 · outbound

This paper cites An improved swin transformer-based model for remote sensing object detection and instance segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images An improved swin transformer-based model for remote sensing object detection and instance segmentation,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.473343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.604281Z digest=sha256:d66ee89b0a198fefccfb18d425c4be799bc08b204116119b142fd23d1ab42709

Observation f7ef6323-9f08-4640-8ad5-7e32f4f9181e · outbound

This paper cites RSPrompter: Learning to prompt for remote sensing instance segmentation based on visual foundation model,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images RSPrompter: Learning to prompt for remote sensing instance segmentation based on visual foundation model,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.460282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.608331Z digest=sha256:745c51b69cbb2ecbc9ee752327ee291e5213f16e1ffdb7e0b2411ccdf697a19d

Observation cbccd2f0-4828-4f41-a40b-5ee24f71063f · outbound

This paper cites Contour Loss: Boundary-Aware Learning for Salient Object Segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Contour Loss: Boundary-Aware Learning for Salient Object Segmentation

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-10T22:56:50.882903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.612500Z digest=sha256:86edb6ffa8c16f3722476bf1edf26ca06f7d84dcc011615009d0f750bcc2569e

Observation 752eb87d-e779-4aab-839c-013dd537b092 · outbound

This paper cites Yolact: Real-time instance segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Yolact: Real-time instance segmentation

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.446670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.617075Z digest=sha256:244c8f0226982cb6600e6f5d844efb20509bb4b4080f6562a133bad77110325e

Observation f51517fb-0ac0-4d99-86fe-52b98e00f521 · outbound

This paper cites Solo: Segmenting objects by locations,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Solo: Segmenting objects by locations,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.433348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.621047Z digest=sha256:b99de6bf4f8aa76e03f653ce34304d1f08fa8e3d4850fff76afe82dcf38925f7

Observation 43957358-6839-4816-a9ed-4f19961a38f8 · outbound

This paper cites Blendmask: Top-down meets bottom- up for instance segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Blendmask: Top-down meets bottom- up for instance segmentation

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.420268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.625042Z digest=sha256:ed2e55dfe4c811427e94f39c4ffd81fe286f65c4200d71e12e1b350be5769306

Observation 3636a34f-1861-4fd5-8701-7f5aa5f8b845 · outbound

This paper cites Conditional convolutions for instance segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Conditional convolutions for instance segmentation

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.405278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.629127Z digest=sha256:cab4cb0cbfa12e3b0a287805911fee92d8d2aea663bc034d377519bcb5254e23

Observation 0130fe6f-d462-4ded-9c77-c80942e980b3 · outbound

This paper cites Mask R-CNN,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Mask R-CNN,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.391484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.633311Z digest=sha256:7b1c96d05ca2fdfcd8872de8764aa978b40f09ab7f5049b96a2e19569a9236cd

Observation e482e935-4b73-4d88-8c68-ad62671a4238 · outbound

This paper cites Faster R-CNN: Towards Real- Time Object Detection with Region Proposal Networks,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Faster R-CNN: Towards Real- Time Object Detection with Region Proposal Networks,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.378233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.637467Z digest=sha256:a5fed22850af2cd8efb2ba3129eee2f37c07f7654817e89faa8f41e28dd874b7

Observation 30db8f1b-b125-4929-bf5e-7c369c3fe303 · outbound

This paper cites Hybrid task cascade for instance segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Hybrid task cascade for instance segmentation,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.364388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.641764Z digest=sha256:e03669e9a3509a54a918cb3f5794a8fc0a1f27993747d6d9d99bc7624ffddf3a

Observation 70666914-f254-4d2b-9b86-cfe8db20e0bf · outbound

This paper cites Path aggregation network for instance segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Path aggregation network for instance segmentation,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.350200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.646217Z digest=sha256:94a4c1192dbd5bb32eaf4ad4b0398385da3a07552012b4ead27eed4cd64c05c9

Observation 656c371d-dd7e-4e01-87fc-fee9ecd42e6b · outbound

This paper cites Global contex t parallel attentio n for anchor-free instance segmentation in remote sensing images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Global contex t parallel attentio n for anchor-free instance segmentation in remote sensing images,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.131117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.714204Z digest=sha256:3cb84b43eecb8bb3edc3047bfa0eefcb85ec11a39b13cf940bdede2654511ec9

Observation 7c80cb23-f73f-4a30-bf46-cd7bc8929d88 · outbound

This paper cites Fas t interactive object annotation with curve-gcn,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Fas t interactive object annotation with curve-gcn,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.321768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.655071Z digest=sha256:6599cb58177f1ea8ad87293795e44e7187acd3569888af6393c37512601be7e3

Observation d7012b3a-51fe-43a8-8063-cd249082e238 · outbound

This paper cites Deep snake for real-time instance segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Deep snake for real-time instance segmentation,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.307229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.659375Z digest=sha256:8b7341c53740a682196cda0fce0f056f75796c7deb1d31cfc357024d97808fde

Observation 7fcb0948-adae-4329-8bc1-98c10ba7f7d8 · outbound

This paper cites Dance: A deep attentive contour model for efficient instance segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Dance: A deep attentive contour model for efficient instance segmentation,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.293120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.663414Z digest=sha256:79d57b7eb0bcf5bab978e680a4909c037d5fa697a1139158ca6e5495730c07c2

Observation c2a8d6ca-35c5-4e68-b138-b5dbbe6a63a7 · outbound

This paper cites Annotating object instances with a polygon-rnn.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Annotating object instances with a polygon-rnn

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.279263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.667713Z digest=sha256:4b25784e2800461e1bf444364a7a6da80fa03b86dca9842ff27c5b63fdb76ff1

Observation ee3b34be-5749-4989-8f97-664d4bf2a9aa · outbound

This paper cites Efficient interactive annotation of segmentation datasets with polygon-rnn++.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Efficient interactive annotation of segmentation datasets with polygon-rnn++

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.266731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.672673Z digest=sha256:d2f1a3d32f45118c5bf7ea86d82d61c41f851c2c1cffffcbb8eb2e5a672bb471

Observation a43db398-f706-4378-804f-db16dd218f70 · outbound

This paper cites HQ-ISNet: High-quality instance segmentation for remote sensing imagery,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images HQ-ISNet: High-quality instance segmentation for remote sensing imagery,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.253682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.676740Z digest=sha256:39371fd736b9ca76c2862c91812b76194c4e1af11a22f9d05f5172f74cb1cc09

Observation 2b33853d-0878-4731-b383-76e75d6248eb · outbound

This paper cites Ship instance segmentation from remote sensing images using sequence local context module.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Ship instance segmentation from remote sensing images using sequence local context module

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.239538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.680930Z digest=sha256:7c7816194927b7532f01fce9e3b0406a2d7e70a9623dda462be351d608f210d4

Observation 2ca882c2-bded-4235-b55c-d7cb4c2e12e6 · outbound

This paper cites DB-BlendMask: Decomposed attention and balanced BlendMask fo r instance segmentation of high- resolution remote sensing images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images DB-BlendMask: Decomposed attention and balanced BlendMask fo r instance segmentation of high- resolution remote sensing images,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.226071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.684907Z digest=sha256:92d9ee49a988588dc87858904aa9995e5f464604013bc1ac338654ccd06acc4d

Observation f539f1b5-8bed-4a27-a7f1-fb5ed55ec6cb · outbound

This paper cites Faster and Better Instance Segmentation for Large Scene Remote Sensing Imagery.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Faster and Better Instance Segmentation for Large Scene Remote Sensing Imagery

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.213131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.689054Z digest=sha256:00ff626a578b36e98246ad8373f4784dab3e191b741a498479db398e82fb3863

Observation 8ec1983c-1c7c-48b6-b3ca-5dc0348cc87d · outbound

This paper cites Precise and robust ship detection for high- resolution SAR imagery based on HR-SDNet,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Precise and robust ship detection for high- resolution SAR imagery based on HR-SDNet,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.200280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.693218Z digest=sha256:a69cc74d5ccd8333cb13feb371811a3511506cde2f11917f2dcd0eaa052eab7a

Observation 7948e64a-1078-4e51-9617-0610546f5007 · outbound

This paper cites Cas cade R-CNN: High quality object detection and instance segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Cas cade R-CNN: High quality object detection and instance segmentation,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.187363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.697471Z digest=sha256:0b4d1f73c2875f0d54bee58b87e2ba8d7885d10d97743285406a7471575e8899

Observation 4936b994-8b71-40fc-8731-15dc60327e9b · outbound

This paper cites OEC-RNN: Object-oriented delineation of rooftops with edges and corners using the recurrent neural network from the aerial images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images OEC-RNN: Object-oriented delineation of rooftops with edges and corners using the recurrent neural network from the aerial images,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.173725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.701723Z digest=sha256:0af41713eb77b495c2ba7e5a4bdd2f765a52f3f2f470b2294cc6a5393bcb59ff

Observation a8410d2e-e04a-4d67-b338-25a488b29364 · outbound

This paper cites Building outline delineation: From aerial images to polygons with an improved end-to-end learning framework,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Building outline delineation: From aerial images to polygons with an improved end-to-end learning framework,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.158170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.705886Z digest=sha256:9fafd46317f20d1b8dd86892b436fa486b6485fdb60d1415187599ed4927fd31

Observation 17151ab3-efaa-4b9f-80e0-e0b31775a6a8 · outbound

This paper cites BuildMapper: A fully learnable framework for vectorized building contour extraction,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images BuildMapper: A fully learnable framework for vectorized building contour extraction,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.143613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.710091Z digest=sha256:6bdc844359aac59e3f86cd54295509f04c1ff79725c7a38d5acd05b6676b327d

Observation 00de2c79-f9ef-4c49-a2aa-b7e6c26652d4 · outbound

This paper cites Attention is all you need,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Attention is all you need,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.954052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.777906Z digest=sha256:50de763b96088a457ab298168b09071a020971ea6d195db567a4e800799329d2

Observation 5bb85fa6-829f-403f-8286-869561bf3d4e · outbound

This paper cites Learning to aggregate multi-scale context for instance segmentation in remote sensing images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Learning to aggregate multi-scale context for instance segmentation in remote sensing images,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.117974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.718325Z digest=sha256:a97d6f74657181b5f3a1960ded72033620a0d2d7a55873c3c5c32e1078c88636

Observation f99b002f-fe85-498b-b082-e6008581aa43 · outbound

This paper cites GLSANet: Global-local self-attention network for remote sensing image semantic segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images GLSANet: Global-local self-attention network for remote sensing image semantic segmentation,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.104329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.722360Z digest=sha256:f3931aa35803e8abbd0d23927a155740f0b044dd71946b00299dd69976ebf256

Observation 50a8c29b-5e07-43a5-9361-6feb153cabb9 · outbound

This paper cites LPASS-Net : Lightweight progressive attention semantic segmentation network for automatic segmentation of remote sensing images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images LPASS-Net : Lightweight progressive attention semantic segmentation network for automatic segmentation of remote sensing images,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.091104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.726405Z digest=sha256:ddf68a3ed8ae067090748ee61f1aecf9fceb45e8b5d895cffc78af54230e479c

Observation f36caa28-9a6e-4455-9cef-87757f43867c · outbound

This paper cites Swin Transformer Embedding UNet for Remote Sensing Image Semantic Segmentation,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Swin Transformer Embedding UNet for Remote Sensing Image Semantic Segmentation,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.077292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.730460Z digest=sha256:ac98673391c2d33b77c6f17e2b6747c88f4ffa944cf601a6b354a714b9b418c7

Observation 5d1e1bd7-79bd-4f68-89a2-c6b228b13cd5 · outbound

This paper cites Swin-transformer-enabled YOLOv5 with attention mechanism for small objec t detection on sa tellite images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Swin-transformer-enabled YOLOv5 with attention mechanism for small objec t detection on sa tellite images,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.064289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.734533Z digest=sha256:c83c5bd72a35a6236091d0b291b6adbe53f03ae1d2942a2812209b3f4a20ddcb

Observation 033cc5c6-6d67-4e06-8658-70f688d5e4f1 · outbound

This paper cites FN" and.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images FN" and

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.647116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.548919Z digest=sha256:f5bcfa510332fe339d8a44df6960ef8f49fecfe8be7f46dda936415ed1146340

Observation 5c731e43-ef83-4781-b94c-89e247d46b8c · outbound

This paper cites Segment anything.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Segment anything

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.051150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.739016Z digest=sha256:6340bc7e3605d531060adbba4eaa6218328a7f118439e19cd7bb65b15fe00fc0

Observation 97afa013-0a40-4ae5-8562-2b67a7db8323 · outbound

This paper cites Gated-scnn: Gated shape cnns for semantic segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Gated-scnn: Gated shape cnns for semantic segmentation

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.037858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.743015Z digest=sha256:1507a60b3e29af58cea00f4a646a23a582b227a7c83c6037e6d429a3d0185981

Observation 9c0a8acb-9c4d-4d68-a86c-f87a0ade2979 · outbound

This paper cites Semantic image segmentation with task-specific edge detection using cnns and a discriminatively trained domain transform.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Semantic image segmentation with task-specific edge detection using cnns and a discriminatively trained domain transform

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.024662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.747121Z digest=sha256:c4ce45c578844b2543723b0aeecabe13ae8a89c078cd17e2a5ae72104efb8713

Observation 0e1a30d9-65a4-43ee-a7e4-60839763a665 · outbound

This paper cites Boundary-preserving mask r-cnn.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Boundary-preserving mask r-cnn

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:51.010174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.751142Z digest=sha256:ebf00ab3ae788d2f7b1b44d0de803e08d682b7b1f9363e0e682107ebd5b84269

Observation 77c8debb-a057-4b23-9e43-0e615b847aa2 · outbound

This paper cites Distance Map Loss Penalty Term for Semantic Segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Distance Map Loss Penalty Term for Semantic Segmentation

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T22:56:50.755260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:56:50.755260Z digest=sha256:c2e542b0b4eaca52d07a4737c495aadb5f6d8d2dcf322b4786846030b90674fb

Observation 2cefa14f-6e73-4ec8-945f-25791b206130 · outbound

This paper cites Boundary loss for highly unbalanced segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Boundary loss for highly unbalanced segmentation

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.996318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.760459Z digest=sha256:6484c2f3dcdd3ce3a13123f30933322359b133d4a8359a8822f6e195447c94c9

Observation 8886b98b-9010-4a0b-b151-48a39bf1d2c8 · outbound

This paper cites A new spatial-oriented object detection framework for remote sensing images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images A new spatial-oriented object detection framework for remote sensing images,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.982952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.765452Z digest=sha256:cb321b48c4ce44417057b8c06d9b8f6170244265d39fe64cca0694e5d9c6a87e

Observation 8a1b6088-b452-4737-ad6f-3f39025ba911 · outbound

This paper cites UNet++: A nested u-net architecture for medical image segmentation.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images UNet++: A nested u-net architecture for medical image segmentation

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.969271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.769478Z digest=sha256:730da708c592f475550abb6ba8cfc735407300a6530d1ee9bcddd408767cbcc4

Observation 93368410-3f02-4a3f-8242-149e21f8124a · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T22:56:50.773332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:56:50.773332Z digest=sha256:4de8a77e9c8e5d956524158ceeefb076190d6902922ace0a5e810c1e0cb44d39

Observation 1e5f2128-084a-41e6-9ce0-c20d6cc9dbce · outbound

This paper cites Fully convolutional networks for multisource building extraction from an open aeri al and satellite imagery data set,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Fully convolutional networks for multisource building extraction from an open aeri al and satellite imagery data set,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.939176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.782228Z digest=sha256:62e2ddafe59688eff9954affc5040f0a5ddc83ec63e1bb14213b9f69edafb694

Observation 288c7786-db54-456a-a9ee-8756492f9945 · outbound

This paper cites A dataset of building instances of typical cities in China,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images A dataset of building instances of typical cities in China,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.924619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.786877Z digest=sha256:4a08d0e7a8fdcce7a7eee96ffd374085ce7ac53efcde0552bc60b9f0c221f52a

Observation c4b84b06-54cc-4dbe-8404-2ba2bc393a7b · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T22:56:50.791217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:56:50.791217Z digest=sha256:7e14a61bc6fe6006d7fc41b34ba3975fe8641fa166094baf3b418642b55c8fca

Observation 83c67ea2-1f70-460f-9c2c-8c226f673db8 · outbound

This paper cites Object detection and instance segmentation in remote sensing imagery based on precise mask R- CNN.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images Object detection and instance segmentation in remote sensing imagery based on precise mask R- CNN

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.910739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.795675Z digest=sha256:e9195628d66631ce0472f5c3f5e9654cc853a9f24edc34d3098a136547bc5218

Observation f657e691-b08f-427a-b7a6-d6fc7dfbff39 · outbound

This paper cites DCTC: Fast and Accurate Contour-Based Instance Segmentation with DCT Encoding for High Resolution Remote Sensing Images,.

A Novel Shape Guided Transformer Network for Instance Segmentation in Remote Sensing Images DCTC: Fast and Accurate Contour-Based Instance Segmentation with DCT Encoding for High Resolution Remote Sensing Images,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:56:50.897404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T22:56:50.799882Z digest=sha256:eb9895833326b2e50871a379c4800a61043e447194a0a9bc900671b80b7f4a03

Pith citing papers

No inbound Pith citation observations are available.