Paper Citation Record · LEDGER

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios

As of 14 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2506.18682.

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

pith.paper-citation-record.v1
2506.18682 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-19T08:16:46.185732Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T23:09:58.563501Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-18T23:11:53.919188Z

Reference resolution

43 of 43 outbound references displayed

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verified fuzzy39
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cd81fe02-fdb2-4d03-900a-324f36203009 · outbound

This paper cites Hsi-drive: A dataset for the research of hyperspectral image processing applied to autonomous driving systems.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hsi-drive: A dataset for the research of hyperspectral image processing applied to autonomous driving systems

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.382340Z

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Observation e573f30e-0b06-4680-a414-22269fa35d35 · outbound

This paper cites Hsi-drive v2. 0: More data for new chal- lenges in scene understanding for autonomous driving.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hsi-drive v2. 0: More data for new chal- lenges in scene understanding for autonomous driving

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.417352Z

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Observation 516ec3e2-c0cc-45c5-b059-3272b2364c38 · outbound

This paper cites Urban scene understanding via hyperspectral images: Dataset and benchmark.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Urban scene understanding via hyperspectral images: Dataset and benchmark

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.403595Z

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Observation a52b3bd4-3585-49e0-87df-543e302222dc · outbound

This paper cites Most relevant spectral bands identification for brain cancer detection using hyperspectral imaging.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Most relevant spectral bands identification for brain cancer detection using hyperspectral imaging

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.426381Z

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Observation e65c8cf6-3d04-495b-b324-1b746523a2c3 · outbound

This paper cites Hyperspectral satellites, evolution, and development his- tory.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hyperspectral satellites, evolution, and development his- tory

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.408573Z

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Observation a60c49fe-6e01-451f-a2d7-65d9e04d6191 · outbound

This paper cites A review of hyperspectral remote sensing and its application in vegetation and water resource studies.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios A review of hyperspectral remote sensing and its application in vegetation and water resource studies

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.398526Z

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Observation 1c452606-f6fa-4893-ba94-2356ded83cab · outbound

This paper cites The properties of the cornea based on hyperspectral imaging: Optical biomedical engineering perspective.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios The properties of the cornea based on hyperspectral imaging: Optical biomedical engineering perspective

Reference 7

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Observation 990f9f13-7584-478b-a574-3ab623ad7920 · outbound

This paper cites Weakly-supervised semantic segmentation in cityscape via hyperspectral image.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Weakly-supervised semantic segmentation in cityscape via hyperspectral image

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.394025Z

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Observation 7baeef16-b0c0-4d0c-87c7-9b831a04c8d9 · outbound

This paper cites Road condition estimation using deep learning with hyperspectral images: detection of water and snow.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Road condition estimation using deep learning with hyperspectral images: detection of water and snow

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.412817Z

Source-reported events for the cited work

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Observation 0f1a6dba-c48c-4f84-94e1-f4c6a7df7ba3 · outbound

This paper cites Exploring fully convolutional networks for the segmen- tation of hyperspectral imaging applied to advanced driver assistance systems.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Exploring fully convolutional networks for the segmen- tation of hyperspectral imaging applied to advanced driver assistance systems

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.421766Z

Source-reported events for the cited work

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Observation 708bde0c-2393-4fc4-b308-426b64d8ef61 · outbound

This paper cites Hs3-bench: A benchmark and strong baseline for hyperspectral semantic segmenta- tion in driving scenarios.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hs3-bench: A benchmark and strong baseline for hyperspectral semantic segmenta- tion in driving scenarios

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.244199Z

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Observation a1d45b70-087f-477b-82ca-9fb3a0eb3e47 · outbound

This paper cites Hyperspectral Imaging-Based Perception in Autonomous Driving Scenarios: Benchmarking Baseline Semantic Segmentation Models.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hyperspectral Imaging-Based Perception in Autonomous Driving Scenarios: Benchmarking Baseline Semantic Segmentation Models

Reference 12

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Observation 1cb663c7-82e9-4cbf-860b-28a9094d75e5 · outbound

This paper cites Imagenet large scale visual recognition challenge.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Imagenet large scale visual recognition challenge

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.240143Z

Source-reported events for the cited work

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Observation d0f17a16-2c96-45ad-b797-90aa71d5efb4 · outbound

This paper cites Dimensionality reduction techniques with hydranet framework for hsi classification.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Dimensionality reduction techniques with hydranet framework for hsi classification

Reference 14

Resolution: malformed identifier; raw_fallback, observed 2026-05-19T08:17:11.319727Z

Source-reported events for the cited work

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Observation c4c4a912-04b4-4f01-9c42-9d6d9718b05d · outbound

This paper cites Impact of dimensionality reduction techniques on classification of hyperspectral images.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Impact of dimensionality reduction techniques on classification of hyperspectral images

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.315449Z

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Observation 66fe5bbf-0c29-4a1b-961c-75ccfe34c137 · outbound

This paper cites Hyperspectral image classification based on multi-scale convolutional features and multi-attention mechanisms.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hyperspectral image classification based on multi-scale convolutional features and multi-attention mechanisms

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.252184Z

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Observation ad2fa970-fcf6-4bd4-bf2a-4462f541eb02 · outbound

This paper cites Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.282806Z

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Observation 26ea8338-ec61-4416-a043-e4043710b556 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios U-net: Convolutional networks for biomedical image segmentation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.291971Z

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Observation 43868209-220a-49f7-9170-5fb2a8076287 · outbound

This paper cites The cityscapes dataset.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios The cityscapes dataset

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.297102Z

Source-reported events for the cited work

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Observation 53f1f9b0-c837-412d-b530-2ccf06c145f1 · outbound

This paper cites Multispectral pedestrian detection: Benchmark dataset and baseline.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Multispectral pedestrian detection: Benchmark dataset and baseline

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.261154Z

Source-reported events for the cited work

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Observation 8b1c81de-37e6-4f13-92b0-3e612b3b37c4 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.371471Z

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Observation a7f59386-e2ba-47b2-8b15-fbbe5ac67824 · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios nuscenes: A multimodal dataset for autonomous driving

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.376157Z

Source-reported events for the cited work

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Observation e8aec0d9-6978-47aa-9b41-6f5eb5fa762b · outbound

This paper cites Hyko: A spectral dataset for scene understanding.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hyko: A spectral dataset for scene understanding

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.362613Z

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Observation c4819edf-fc68-4c78-b958-574c11e2c07b · outbound

This paper cites Hsi road: a hyper spectral image dataset for road segmentation.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hsi road: a hyper spectral image dataset for road segmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.265337Z

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Observation 433614eb-8f57-489d-8ed2-78de9e1cd9c7 · outbound

This paper cites Hyper- drive: Visible-short wave infrared hyperspectral imaging datasets for robots in unstructured environments.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hyper- drive: Visible-short wave infrared hyperspectral imaging datasets for robots in unstructured environments

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.269722Z

Source-reported events for the cited work

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Observation 9b412059-d606-4f53-b775-c9791d4b7f1c · outbound

This paper cites Hyperspectral imaging for mobile robot navigation.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hyperspectral imaging for mobile robot navigation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.323569Z

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Observation 0ab24307-1692-42dd-a2e3-36eeefd10383 · outbound

This paper cites Dual fusion network for hyperspectral semantic segmentation.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Dual fusion network for hyperspectral semantic segmentation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.356973Z

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Observation b5109b44-ecd0-4808-b518-1a2cefc95bcc · outbound

This paper cites 3-d deep learning approach for remote sensing image classification.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios 3-d deep learning approach for remote sensing image classification

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.248163Z

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Observation 25fab4cd-1f1e-432a-8880-219be548b55e · outbound

This paper cites Deep learning for classifi- cation of hyperspectral data: A comparative review.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Deep learning for classifi- cation of hyperspectral data: A comparative review

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.351962Z

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Observation fbd2d67d-6d56-4983-85b9-bca87b6a31d5 · outbound

This paper cites SpectralZoom: Efficient Segmentation with an Adaptive Hyperspectral Camera.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios SpectralZoom: Efficient Segmentation with an Adaptive Hyperspectral Camera

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:17:10.862454Z

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Observation c90cd727-f43e-4085-8923-422460cdcabc · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.274237Z

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Observation 05e18c50-d3bc-45a2-8957-5c12643d3dde · outbound

This paper cites High-Resolution Representations for Labeling Pixels and Regions.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios High-Resolution Representations for Labeling Pixels and Regions

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-19T08:17:10.874810Z

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Observation 06c3fe15-b532-4465-beff-082680612b18 · outbound

This paper cites Pyramid scene parsing network.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Pyramid scene parsing network

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.278623Z

Source-reported events for the cited work

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Observation be636829-0e2e-4a23-8a28-52fc2459620a · outbound

This paper cites Cbam: Convolutional block attention module.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Cbam: Convolutional block attention module

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.302651Z

Source-reported events for the cited work

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Observation 2068d970-273c-4fa8-951f-453a056c25ff · outbound

This paper cites Coordinate attention unet.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Coordinate attention unet

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.343180Z

Source-reported events for the cited work

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Observation c7097614-9545-412e-bc20-a384e4bdadb9 · outbound

This paper cites Hyperspectral image segmentation: a comprehensive survey.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Hyperspectral image segmentation: a comprehensive survey

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.339004Z

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Observation 11ce49ae-9ba5-47e1-a442-ee6d5bf0ce5d · outbound

This paper cites V oxnet: A 3d convolutional neural network for real-time object recognition.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios V oxnet: A 3d convolutional neural network for real-time object recognition

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.256680Z

Source-reported events for the cited work

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Observation 906a08a5-ce84-424f-9d52-fe8d29cbfeef · outbound

This paper cites A joint network of 3d-2d cnn feature hierarchy and pyramidal residual model for hyperspectral image classification.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios A joint network of 3d-2d cnn feature hierarchy and pyramidal residual model for hyperspectral image classification

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.328401Z

Source-reported events for the cited work

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Observation 6a6e74b9-839b-43e2-be1c-d55ac979937f · outbound

This paper cites Attention is all you need.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Attention is all you need

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.367013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 10e23ab7-85bd-4f28-a6fb-0c1c9ee37b8c · outbound

This paper cites Attention residual hybrid network for unmanned aerial vehicles hyperspectral image classification.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Attention residual hybrid network for unmanned aerial vehicles hyperspectral image classification

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.347648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 09e90463-288f-4a25-81c9-78eb8ce0cdaa · outbound

This paper cites Rectifier nonlinearities improve neural network acoustic models.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Rectifier nonlinearities improve neural network acoustic models

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.310601Z

Source-reported events for the cited work

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Observation 6567baa0-49a5-4a91-b0d1-a4d3700f3494 · outbound

This paper cites Adabelief optimizer: Adapting stepsizes by the belief in observed gradients.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Adabelief optimizer: Adapting stepsizes by the belief in observed gradients

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.331669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 91ccb75d-daed-48d5-adeb-30e5f3b101a1 · outbound

This paper cites Unified focal loss: Generalising dice and cross entropy-based losses to handle class imbalanced medical image segmentation.

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios Unified focal loss: Generalising dice and cross entropy-based losses to handle class imbalanced medical image segmentation

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T08:17:11.335206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

Observation 2efa44c0-c4c8-4bf1-a24f-c204f091f3d2 · inbound

CSNR and JMIM Based Spectral Band Selection for Reducing Metamerism in Urban Driving cites this paper.

CSNR and JMIM Based Spectral Band Selection for Reducing Metamerism in Urban Driving Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-18T23:11:53.921819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.