Pith. sign in

Paper Citation Record · LEDGER

Improving Object Detection by Modifying Synthetic Data with Explainable AI

As of 18 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 0 inbound Pith citation observations for arXiv:2412.01477.

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

pith.paper-citation-record.v1
2412.01477 v3

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:21:28.205834Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

77 of 77 outbound references displayed

  • verified exact0
  • verified fuzzy59
  • unresolved17
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 11bc3242-e8a5-4070-aed3-de94af7a42ae · outbound

This paper cites Generating Synthetic Data in Finance: Opportunities, Chal- lenges and Pitfalls.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Generating Synthetic Data in Finance: Opportunities, Chal- lenges and Pitfalls

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:30.171058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.724514Z digest=sha256:31726eba18d37599a35f71d31ec777fd0fb6562e3efba502287a2eaa7c5be897

Observation 451c0f50-b9bc-4463-9bc8-738e8dc8f43e · outbound

This paper cites Bridging the Domain Gap Between Synthetic and Real-World Data for Autonomous Driving.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Bridging the Domain Gap Between Synthetic and Real-World Data for Autonomous Driving

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:30.146041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.729496Z digest=sha256:9e648849f752b4422eff94ec1f478ad87527c56f7e51d08fc743b65c6a586bc3

Observation 7f04087b-44d4-4435-a593-9c5bb3cfea09 · outbound

This paper cites Narrowing the Semantic Gap Between Real and Synthetic Data.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Narrowing the Semantic Gap Between Real and Synthetic Data

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:30.115774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.736116Z digest=sha256:7dd19eab4d4a5d37ac8eadf439b76af5eb8b1e86993a0e4aa1ddcb89a4cf9c78

Observation cdc407a4-a053-4c2c-9cd9-3ca2b92b42de · outbound

This paper cites Mechanistic Inter- pretability for AI Safety - A Review.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Mechanistic Inter- pretability for AI Safety - A Review

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:30.083733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.740806Z digest=sha256:cf7b8960bb362b599444906a61f9062d4c361f370253bf1d94357d259e1e1bbb

Observation 2e5d2d4c-1209-4b21-bbde-35d47dfd5f2d · outbound

This paper cites Unity Perception: Generate Synthetic Data for Computer Vision.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unity Perception: Generate Synthetic Data for Computer Vision

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:27.745361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:27.745361Z digest=sha256:0bb32bef41c80425d093022a430da4c14215a2a85940911f6a985ce9afec3346

Observation ad7ac8ea-59d3-41d3-83a5-01178211de71 · outbound

This paper cites Advanced Automatic Target Recognition (ATR) with Infrared (IR) Sensors.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Advanced Automatic Target Recognition (ATR) with Infrared (IR) Sensors

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:30.042304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.749726Z digest=sha256:f478b9df959736f5926cc5027fb764e6d2df60bd647d155a80e1c3418b09dcd6

Observation 282caf8a-ef63-4d6a-98c0-3cd0bccac788 · outbound

This paper cites Stargan: Unified Gen- erative Adversarial Networks for Multi-domain Image-to- image Translation.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Stargan: Unified Gen- erative Adversarial Networks for Multi-domain Image-to- image Translation

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:30.019419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.753751Z digest=sha256:3be858361ea36d45be028f7a1ee160563e1ed1aac301531640f22a496a04db7c

Observation 6c0f727e-6442-4bfe-b2ac-3aa4326eafff · outbound

This paper cites Next- Generation Deep Learning Based on Simulators and Syn- thetic Data.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Next- Generation Deep Learning Based on Simulators and Syn- thetic Data

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.989914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.759729Z digest=sha256:a076d7e0a212bf14e0a44a390f3002cdeb57728eed93c842fb6dd9ed79a95da6

Observation a3eafd6c-bd48-4e19-af0e-1719866e3a84 · outbound

This paper cites Exploring Synthetic Data for Ar- tificial Intelligence and Autonomous Systems: A Primer,.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Exploring Synthetic Data for Ar- tificial Intelligence and Autonomous Systems: A Primer,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.962834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.763968Z digest=sha256:7b21d36102c7e410dea90d5a9bf5ba41cd72e91b845d82843e34b0c477ecad29

Observation 717ea6cc-1766-4b80-a2b4-7e9f64730956 · outbound

This paper cites https://dsiac.org/databases/atr-algorithm- development-image-database/, 2014.

Improving Object Detection by Modifying Synthetic Data with Explainable AI https://dsiac.org/databases/atr-algorithm- development-image-database/, 2014

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.945369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.772360Z digest=sha256:e12f99aa5adffeeeb166c8267128c21e9f8c2f3b883989951d18dff45a37c535

Observation 6011c310-541e-45d0-b7c3-72b7c99f88c2 · outbound

This paper cites Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:27.778225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:27.778225Z digest=sha256:45591e5590d8976466f647dda93bae7d710370b0133d1f65f32bc786eb267c94

Observation 5690386f-215b-4761-bc7e-bd0f0b30aff8 · outbound

This paper cites Adaptive Testing of Computer Vision Models.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Adaptive Testing of Computer Vision Models

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.913687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.784003Z digest=sha256:562a1d32d3fd39bdd5f4da7437d3601f5a11ed9a37c65d066fe6e489e0eec1a6

Observation 2cd1fe5d-7e45-4a3f-84b3-0adee5ef18c0 · outbound

This paper cites Harnessing the Power of Synthetic Data in Healthcare: Innovation, Application, and Privacy.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Harnessing the Power of Synthetic Data in Healthcare: Innovation, Application, and Privacy

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.868472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.792264Z digest=sha256:3f09e48f9f980bca8c6c1ccfaf56c99d8d68bae75ae7dc721aad22a1e38a7596

Observation 227f10df-2c2e-4cfd-ab03-f197694e7333 · outbound

This paper cites HaDR: Applying Domain Randomization for Gen- erating Synthetic Multimodal Dataset for Hand Instance Segmentation in Cluttered Industrial Environments.

Improving Object Detection by Modifying Synthetic Data with Explainable AI HaDR: Applying Domain Randomization for Gen- erating Synthetic Multimodal Dataset for Hand Instance Segmentation in Cluttered Industrial Environments

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:27.802231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:27.802231Z digest=sha256:4c50fda48a693eae084b7e8d13e0134ad1d7bc08add0a94d08fe454d12186a4d

Observation 71e85afc-8bac-4b6c-8604-b6e2adf33a33 · outbound

This paper cites Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:27.806715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:27.806715Z digest=sha256:12cbc2742d2d5ae1c13f069aacd690f1bed38fb65ca94089a3fdbb2ed1e98d78

Observation 1fa2bd1b-bb18-465a-b991-cffd10f01433 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 16

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:29.846688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.814766Z digest=sha256:f815fac1f5a49a2ebb06acd5ff15fd4ce43d025f9a15293f08ecca86259d85ae

Observation da0f4d58-de2d-4363-b17c-b3dd40f954f4 · outbound

This paper cites Synthetic Data: Development Status and Prospects for Military Applications.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Synthetic Data: Development Status and Prospects for Military Applications

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.830732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.821804Z digest=sha256:8f4cef9f97731697964ff4c11d611ef7ec0a862b3ee93c8a0f2cad72428b37ec

Observation 60da9314-7eec-4662-b3a5-88811243c1e8 · outbound

This paper cites Image-to-image Translation with Conditional Adver- sarial Networks.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Image-to-image Translation with Conditional Adver- sarial Networks

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.813939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.827454Z digest=sha256:878706cf84238446f73702bf88b382f40cd0bc420721aff2a23d8e2889fe7138

Observation 593ec48b-fff8-4b85-a42a-9f7acbdac55f · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:29.781256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.844630Z digest=sha256:12cc308e40eb8e3fd8211e903985b65c2add4f74bbc203b37105416914cd0a0c

Observation 56cc6e1f-7cac-4b69-b8e6-1c3237d6eb32 · outbound

This paper cites A Style- based Generator Architecture for Generative Adversarial 9 Networks.

Improving Object Detection by Modifying Synthetic Data with Explainable AI A Style- based Generator Architecture for Generative Adversarial 9 Networks

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.763073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.852927Z digest=sha256:78a8ea9ffcc9d182243f4f14222c0f36492b3901901e0123cae7c74879130dfb

Observation dbbea6c1-19e4-4262-9262-b2b63a75f102 · outbound

This paper cites On Convergence and Stability of GANs.

Improving Object Detection by Modifying Synthetic Data with Explainable AI On Convergence and Stability of GANs

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:27.860908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:27.860908Z digest=sha256:eede32ffe6d67d9e48c23cfbca5dacbf1457b8b101739d7d309ca9ea39e5afcc

Observation bc21b0d2-decb-446d-8fa3-f866a019f762 · outbound

This paper cites Closing the Domain Gap: Blended Synthetic imagery for climate object detection.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Closing the Domain Gap: Blended Synthetic imagery for climate object detection

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.739208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.866201Z digest=sha256:9bb228685ad96fd1ab9290d8f65e921668e6702cbbadf6d232eeda3ec45ac6c5

Observation f02a3ffd-e333-40fd-87b2-e628378e7a4a · outbound

This paper cites Mode Collapse in Generative Adversarial Networks: An Overview.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Mode Collapse in Generative Adversarial Networks: An Overview

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.711821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.878577Z digest=sha256:9b3dec36d14fc74143abc636f653c2bc2fa8106e31e23059ad00ca55aca802ac

Observation f69abf5e-f8fd-40dc-a89f-97b44b235504 · outbound

This paper cites Applica- tions, challenges, and future directions of human-in-the-loop learning.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Applica- tions, challenges, and future directions of human-in-the-loop learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.694939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.884645Z digest=sha256:a5c3eaa44f6adc005faa46610cf0e6598b7697b1ad1ec379ef9486f90633fe6d

Observation 901cb9ea-6a60-4884-9203-9f2c23ba6b9d · outbound

This paper cites BSED: Baseline Shapley-Based Explainable Detector.

Improving Object Detection by Modifying Synthetic Data with Explainable AI BSED: Baseline Shapley-Based Explainable Detector

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.676706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.889357Z digest=sha256:f81fc04f67694396cc077994e5eab5004a20b8fefe731f0fed137a12c4bf4992

Observation ca82327a-371d-4911-b414-9b11b944fbf3 · outbound

This paper cites Zhang, Federica Sarro, Ying Zhang, and Xuanzhe Liu.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Zhang, Federica Sarro, Ying Zhang, and Xuanzhe Liu

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.659338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.899673Z digest=sha256:2f32caf4a031034dd5f7ed39ee38e790f355252dd044dcc25d0ddad4b9547867

Observation 775b4070-9317-4dff-a88f-67c9bd55931f · outbound

This paper cites GLIGEN: Open-Set Grounded Text-to-Image Generation.

Improving Object Detection by Modifying Synthetic Data with Explainable AI GLIGEN: Open-Set Grounded Text-to-Image Generation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.640493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.904521Z digest=sha256:fa327c508af9dc7c84e4ef7c8678e413bfb379ea30f81773480836d881dc5312

Observation ce94360e-b735-4e34-9535-f65454ea7f04 · outbound

This paper cites Lundberg and Su-In Lee.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Lundberg and Su-In Lee

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.621453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.910222Z digest=sha256:257b0405d38b7fda9f7eb63c5e2346b3930207d88dd82134838dca9912bc09df

Observation 5d7bfd99-eae4-4fa3-b622-19ac1aa72f77 · outbound

This paper cites A Comparison of Target Detection Algorithms Using DSIAC ATR Algo- rithm Development Data Set.

Improving Object Detection by Modifying Synthetic Data with Explainable AI A Comparison of Target Detection Algorithms Using DSIAC ATR Algo- rithm Development Data Set

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.599858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.916445Z digest=sha256:96781a986e58187e7957e6c22cd052cf1aff8249db95dd55b123d305dc30985a

Observation e5d1d17d-d397-4ce6-9aa2-e9039ad15b8f · outbound

This paper cites The best of Two Worlds: Reprojecting 2D Image Annotations onto 3D Models.

Improving Object Detection by Modifying Synthetic Data with Explainable AI The best of Two Worlds: Reprojecting 2D Image Annotations onto 3D Models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.579191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.924288Z digest=sha256:baf74a599e1c1a07a33c8265f7035b89d39e1080044089bb5dce869626c763ea

Observation da90f6b7-0d09-42ee-9de8-297fc93ace4d · outbound

This paper cites The ETS2 Dataset, Synthetic Data from Video Games for Monocular Depth Estimation.

Improving Object Detection by Modifying Synthetic Data with Explainable AI The ETS2 Dataset, Synthetic Data from Video Games for Monocular Depth Estimation

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.548724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.928736Z digest=sha256:b23c645b5756fc1aff12f32cf014d60c8417ddc197d3d06cf98a6782dae08f7e

Observation ba2cae2f-08a1-44ec-897c-9eb51cd8e477 · outbound

This paper cites Mitigating the Risk of Artificial Intelligence Bias in Cardiovascular Care.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Mitigating the Risk of Artificial Intelligence Bias in Cardiovascular Care

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.520371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.933139Z digest=sha256:1654377c18efa822a645671bd6370185c424d11ba95625f56376f71be43afa0b

Observation 3ead733b-7e2f-4d50-a33f-4429ec06ac0a · outbound

This paper cites Interpretable Machine Learning.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Interpretable Machine Learning

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.471819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.938135Z digest=sha256:b0d48cb30ece75849e6479e666da71f99611ef0168b5bfce9fbed8061c24ba59

Observation ced9da1a-9a33-4006-8c42-2dc39ed94cd5 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:29.447465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.943142Z digest=sha256:71dd37d8071c4ec526d31b7f25764855961bbe72ed801114e826ed349b8f8da3

Observation a1421c30-be76-4ee4-b05e-17a9c57d34a6 · outbound

This paper cites Analyzing DSIAC ATR Algorithm Development Database Utilizing Transfer Learning.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Analyzing DSIAC ATR Algorithm Development Database Utilizing Transfer Learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.426803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.950934Z digest=sha256:5d0d4b56697622b24c69da309768cb01b5ad2acd18b7ad2ecf599d1d0a070bff

Observation 5b3e7b63-b823-448d-b649-d663d7337d14 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:29.405211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.955350Z digest=sha256:d235b0d62deae472ba30053898657dddc55788081e2f771215bc1cd22549eafe

Observation 93c7fb5c-08eb-486c-af98-14cf287d565e · outbound

This paper cites On Domain Randomization for Object De- tection in Real Industrial Scenarios Using Synthetic Images.

Improving Object Detection by Modifying Synthetic Data with Explainable AI On Domain Randomization for Object De- tection in Real Industrial Scenarios Using Synthetic Images

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.376666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.959677Z digest=sha256:fbc3a9fba06306f6fb5bd5d0f712d21e1d911f3b135af03d14628d1ee9851be8

Observation da3bf578-6f50-412b-a5c6-8dc6c605e029 · outbound

This paper cites Priddy and Sastry Dhara.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Priddy and Sastry Dhara

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.355732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.963729Z digest=sha256:5701554564bcaf3ed560a83a5a74cacf4cffaed1a71e016e544fe68a31857b97

Observation d07dc29b-3c81-43b4-ad7c-a1d9c26da186 · outbound

This paper cites https://unity.com/features/probuilder, 2018.

Improving Object Detection by Modifying Synthetic Data with Explainable AI https://unity.com/features/probuilder, 2018

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.335563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.968256Z digest=sha256:8ab7efcf3c42e02aa60fcbfe8b3bf21ae655e87dd6dc57d139ec0c82e1a541fd

Observation de1a7417-b547-4b1d-8030-4a53a1c79164 · outbound

This paper cites Unrealcv: Connecting Com- puter Vision to Unreal Engine.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unrealcv: Connecting Com- puter Vision to Unreal Engine

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.313553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.973012Z digest=sha256:476231d381fa16e5fef2d252ad2def89b12bd4ba26ae44c998f44f1af50e5712

Observation 0d4e5f03-4449-4100-ad30-c4d43df278a3 · outbound

This paper cites Unrealcv: Vir- tual Worlds for Computer Vision.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unrealcv: Vir- tual Worlds for Computer Vision

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.296587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.977159Z digest=sha256:f5d9542ad73cfcfa1d9caf26d3bbf6b3f2eb8212ab8dd46e9363505a4fcb400e

Observation eb6d5829-0995-4fa2-9322-783b8f1a5f8b · outbound

This paper cites Zero-shot Text-to-image Generation.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Zero-shot Text-to-image Generation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.275073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.982264Z digest=sha256:c1a6c24796b2084793c7459680df5fb8fb2e5714af4d20108a9d77e657a68df8

Observation 2922af89-ef98-4d00-b276-2878c076fad5 · outbound

This paper cites SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization.

Improving Object Detection by Modifying Synthetic Data with Explainable AI SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:27.988941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:27.988941Z digest=sha256:2c036400a6207b46c9cdfde2c8a0abe0d4c1be5d592776261f067d7c40b5f48d

Observation c83eaf5f-da8c-49b1-92af-26d915a87997 · outbound

This paper cites Adaptive testing and debugging of NLP models.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Adaptive testing and debugging of NLP models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.253366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:27.994241Z digest=sha256:bc9255646d3fa0625fa30c6b85fe2181f35ec0d699e8c6dbb981d4537574de8b

Observation 24d0b24a-9949-4b69-ab7b-12c983984efd · outbound

This paper cites Beyond accuracy: Behavioral testing of nlp models with checklist.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Beyond accuracy: Behavioral testing of nlp models with checklist

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.233357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.006712Z digest=sha256:b3ce3b3e162b7cb1a4ee2ee23319ccfcb55fb3e16f3c9922294c95a2ab3fda73

Observation 9d0f4c89-de19-4906-aa5b-4f8f73c4159f · outbound

This paper cites High-resolution Image Synthesis with Latent Diffusion Models.

Improving Object Detection by Modifying Synthetic Data with Explainable AI High-resolution Image Synthesis with Latent Diffusion Models

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.192621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.011751Z digest=sha256:63c8628c33f5537338b280c904762fcd7d063f5adb075eeb765e6c40af87c906

Observation 899bf70d-4ca5-4350-a00b-e1b5fe251927 · outbound

This paper cites Synthetic Data Generation with Unity 3D and Unreal Engine for Con- struction Hazard Scenarios: A Comparative Analysis.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Synthetic Data Generation with Unity 3D and Unreal Engine for Con- struction Hazard Scenarios: A Comparative Analysis

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.167852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.017228Z digest=sha256:70c6610070b4b6d1fa19a05487d8cf5dcdfd2490f9caa75d291ed50faaed4a85

Observation f4a2048f-794b-4f7b-bc33-ae7074b6ad2f · outbound

This paper cites Seman- tic Foggy Scene Understanding with Synthetic Data.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Seman- tic Foggy Scene Understanding with Synthetic Data

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.138160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.021395Z digest=sha256:fedad8d2161bb7aefce346d5f8294d8d4eb8d05b8c29358cb8e203a9d51d499b

Observation 0d9a8dc2-91b2-425f-93de-19f45bae3a94 · outbound

This paper cites Nasrabadi, and Raghuveer M.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Nasrabadi, and Raghuveer M

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.120649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.026707Z digest=sha256:6ac75272b0a7921450e7a238d7bde3aa8b441052ecce265cdddb7b7871f604b9

Observation 5b7db30f-96e7-4ee6-b9d8-6fbaae85c55f · outbound

This paper cites A Value for N-Person Games.

Improving Object Detection by Modifying Synthetic Data with Explainable AI A Value for N-Person Games

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.100022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.030924Z digest=sha256:ff8c6da76f3bf2d2cb814b457c593c0f8c749f0d8f45669b72f9bd0f58b948b2

Observation 6fbaa42d-eae6-4b0e-8865-39e2dd3678e0 · outbound

This paper cites Automatic Virtual 3D City Generation for Synthetic Data Collection.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Automatic Virtual 3D City Generation for Synthetic Data Collection

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.079542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.037638Z digest=sha256:3c136f86a81549bf315e218d635f92393f3fd4493a91903a40660df09b3db5c8

Observation a84b0c8b-450e-4b0a-b53c-ac60ea89d2b5 · outbound

This paper cites Rareplanes: Synthetic Data Takes Flight.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Rareplanes: Synthetic Data Takes Flight

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.061238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.044131Z digest=sha256:cc57d510aeec04bcbaa2f3a9c595aeabebe4252c0b5dcedfbcec224df88b00a6

Observation 0a98a1e5-9af3-455c-a209-76c60943b819 · outbound

This paper cites Girshick.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Girshick

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.042524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.051587Z digest=sha256:715efd82ea7ccaa5d00a4b8a46e4f52a0e4380f3544eba17ba3de650e17fcf69

Observation d34f7841-2674-4027-84ae-ac101fba545c · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

Improving Object Detection by Modifying Synthetic Data with Explainable AI The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:28.056196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:28.056196Z digest=sha256:78e94d4aae367a566d1eb69b15e9de5b629eb9b84a6c1cdc069b95e25ea21e86

Observation 1f49af5c-1686-4929-ad60-09b346801611 · outbound

This paper cites The Rise of Synthetic Data: Enhancing AI and Machine Learning Model Training to Address Data Scarcity and Mitigate Privacy Risks.

Improving Object Detection by Modifying Synthetic Data with Explainable AI The Rise of Synthetic Data: Enhancing AI and Machine Learning Model Training to Address Data Scarcity and Mitigate Privacy Risks

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.023993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.063773Z digest=sha256:c9bd7b8c3d40be768c83e5707bb54404f9c4b9b2a44ba88c6c7f00df8adb2743

Observation 598602d1-fc4b-4463-9300-d1024d1ce51f · outbound

This paper cites Daniel Freeman, Theodore R.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Daniel Freeman, Theodore R

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:29.007571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.068137Z digest=sha256:cfb3c662cdee55212e3f893b4d50a5d095df3b66f3f9596bccff19cb5372a808

Observation 3061b979-d100-4228-83fb-76738322623a · outbound

This paper cites Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.983508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.072799Z digest=sha256:98e7384821261c4a1cc82e1e9f55bdcfea1ff150ca8a0e1f6d2d5fb82f812290

Observation 8eafb941-cff4-475a-8994-673ce06ab20e · outbound

This paper cites https://unity.com/.

Improving Object Detection by Modifying Synthetic Data with Explainable AI https://unity.com/

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.967654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.078510Z digest=sha256:7178d0d44c97223bb0fe6309914360622883e28098da2a981bacb090defa7b02

Observation dc0b0e22-d4a7-4c51-90ce-f96c01173117 · outbound

This paper cites Yolov8: A novel object detection algorithm with enhanced performance and robust- ness.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Yolov8: A novel object detection algorithm with enhanced performance and robust- ness

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.947537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.083708Z digest=sha256:24aecb6649932b8a8a9195f0ba0ece33fe085ff6b3cec597c5adc6eca2ee01ab

Observation f4e89774-5f95-4c14-9e8c-8d149e1b1fec · outbound

This paper cites Learning from Synthetic Humans.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Learning from Synthetic Humans

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.932226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.091264Z digest=sha256:e1f1005d39f9ef3057b4dfb7a2f210784fe77a2a78ed909ddab8ddc393c47860

Observation 622ce436-c7fe-4b00-9827-056c200b3901 · outbound

This paper cites Wang, E.P.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Wang, E.P

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.906219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.105171Z digest=sha256:09d0926061f08b596ab093a7e93cd199c60b2d4fe3c0718975ca5d415f7f8ff9

Observation acd68d9e-a50b-4fdd-84a0-c8b04cbff3ab · outbound

This paper cites Bovik, H.R.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Bovik, H.R

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.889936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.116827Z digest=sha256:a20c0616f9559ba247dd61b05d24556d5db90eed6123a6eb6420e66d90b8146e

Observation 4d365dd0-5cf5-4974-ba60-6b9066adc2f2 · outbound

This paper cites Diffusion-GAN: Training GANs with Diffusion.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Diffusion-GAN: Training GANs with Diffusion

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-12T04:21:28.121374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:28.121374Z digest=sha256:d300ea274659f00fba910e057d8c3fd00e4d9845b0977c32e7e5aeae50825ec5

Observation 7c7f082a-6afb-41a7-8e4c-99af2b0eed99 · outbound

This paper cites Dis- covering bugs in vision models using off-the-shelf image generation and captioning.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Dis- covering bugs in vision models using off-the-shelf image generation and captioning

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.871161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.126674Z digest=sha256:ab4485cd8624d701372c383f8ddd7e6bed1ffc48bbb33578bad318e01a6bbba4

Observation 02173675-46b9-4739-8c58-146d2a594d4b · outbound

This paper cites A survey of human-in-the-loop for machine learning.

Improving Object Detection by Modifying Synthetic Data with Explainable AI A survey of human-in-the-loop for machine learning

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.847545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.130988Z digest=sha256:c1df3adf94184c1f09a56fbd221c78b9884c3197ff5b0f2bb346a000294af9f6

Observation 4e77ddbb-7db7-4187-b3f6-acc880b99709 · outbound

This paper cites VarifocalNet: An IoU-aware Dense Object Detec- tor.

Improving Object Detection by Modifying Synthetic Data with Explainable AI VarifocalNet: An IoU-aware Dense Object Detec- tor

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.826466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.136173Z digest=sha256:c89a42db3c10eba44c225b9d2e13cd23b5bea7fb30e50cfd28425306cd0a3583

Observation 8f58f0e5-dbab-4cfa-9078-e0072177441f · outbound

This paper cites Efros, Eli Shecht- man, and Oliver Wang.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Efros, Eli Shecht- man, and Oliver Wang

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.802692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.140616Z digest=sha256:d872cb53d9bfe5efcb6ea4cbe4423a6bdf4a85f1a408a337265777d47fa3ff45

Observation 4c93dad5-2104-41b0-a43a-14d06ce5df2b · outbound

This paper cites Unpaired Image-to-image Translation Using Cycle- Consistent Adversarial Networks.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unpaired Image-to-image Translation Using Cycle- Consistent Adversarial Networks

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.784685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.146350Z digest=sha256:b3a970b24108e266bec90bb1a769bf007ee4b6f15c006b5ec58e7c7df5482816

Observation f91599b1-cb28-4a28-94b1-ae72e25a22d3 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 70

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:28.766649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.150256Z digest=sha256:fd1dac05b802a75474a665a49a3df6100d535e14718b4bd07b5d723c535053b8

Observation dba1fd18-8fc6-4793-a1e9-014a4f34e13c · outbound

This paper cites Example plots of SHAP contributions of pixels to out- puts of models trained on (a) real data only and (b) real + synthetic v0 (initial) data, for a single test image of a ZSU23.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Example plots of SHAP contributions of pixels to out- puts of models trained on (a) real data only and (b) real + synthetic v0 (initial) data, for a single test image of a ZSU23

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.733904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.156930Z digest=sha256:0c877292950c4d00eb43e5a3dfd7c4df3592436acb81311ca23a5a7b9111272f

Observation 8fd4422b-65d6-45fd-a701-882e21207f29 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:28.711301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.162540Z digest=sha256:e332126375c220bf0f654322e26145f7bcbb7217dc635f32ba234576292f105f

Observation d9711253-5f20-46f0-aac6-d21fb70ca845 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 73

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:28.692173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.169121Z digest=sha256:f5ecb3cd79174062721db2ed7a8f05226badf46e924d89d141b9ad9dc716bc3a

Observation e5fd9672-89ae-4e88-83ce-5e634452bc44 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 74

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:28.667507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.175534Z digest=sha256:af1c0dc1fc4e076ffdcac501e31ceb749e32ab9f8cf28d5471b52930ee5d9ac5

Observation 4b32aa7b-745c-4e36-84cd-b560a711a2a3 · outbound

This paper cites First, we consider the effect of the ratio of real and syn- thetic data for fixed dataset size.

Improving Object Detection by Modifying Synthetic Data with Explainable AI First, we consider the effect of the ratio of real and syn- thetic data for fixed dataset size

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.643354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.188137Z digest=sha256:4b2bb6c5b13d88080bdee34d1ad897b8b1bc26eec6c1a65cab693e47b978d91e

Observation 55f1dfff-60b7-47e1-aca6-466ee62118b0 · outbound

This paper cites In this dataset we have a nat- ural dimension of variation (orientation of the vehicle), and so we do not need to cluster the samples to explore the di- mension of variation.

Improving Object Detection by Modifying Synthetic Data with Explainable AI In this dataset we have a nat- ural dimension of variation (orientation of the vehicle), and so we do not need to cluster the samples to explore the di- mension of variation

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:21:28.619557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.197380Z digest=sha256:360a53b9ec704f9ffff1d24c848d6f2933ee5925658e11bd8607397aa60d2516

Observation 94fbca3c-f0e2-4c49-94fe-780e4c611e4a · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 77

Resolution
unresolved
raw_fallback, observed 2026-08-12T04:21:28.588963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:21:28.205834Z digest=sha256:fa53e02434eea45ac6ce9dc3ffe547e77378eb2db34aeac3b7c0f01beba31378

Observation 5cd2d193-cce2-4424-9fbd-d5164393bac3 · outbound

This paper cites an unresolved cited work.

Improving Object Detection by Modifying Synthetic Data with Explainable AI Unresolved cited work

Reference 2023

Resolution
parse uncertain
no resolver link, observed 2026-08-12T04:21:27.788276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:21:27.788276Z digest=sha256:1432c6c8968ce1fe47aa848a954863a7d0a9bd1610a8689c84e1ca24142e7fcd

Pith citing papers

No inbound Pith citation observations are available.