Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach | Paper Citation Record

Observation 9da216e8-4726-45f8-b2e2-14bd3a6594d0 · outbound

This paper cites Fully Convolutional Networks for Semantic Segmentation.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Fully Convolutional Networks for Semantic Segmentation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.073190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d96de5d-23a9-45a1-b894-7a65ab40a7c5 · outbound

This paper cites Review the State-of-the-art Technologies of Semantic Segmentation Based on Deep Learning.Neurocomputing, 493:626–646, 2022.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Review the State-of-the-art Technologies of Semantic Segmentation Based on Deep Learning.Neurocomputing, 493:626–646, 2022

Reference 2

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.566748Z

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.

Observation 58b24b1b-6c8f-4d52-8e58-ddad9e8d32a1 · outbound

This paper cites Deep Learning in Medical Hyperspectral Images: A Review.Sensors, 22(24):9790, 2022.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Deep Learning in Medical Hyperspectral Images: A Review.Sensors, 22(24):9790, 2022

Reference 3

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.556421Z

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.

Observation 3ff4ad17-7983-4cd7-9845-b34d40fc89c5 · outbound

This paper cites Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review.Sensors, 22(3):757, 2022.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review.Sensors, 22(3):757, 2022

Reference 4

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.545652Z

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.

Observation 74d017bb-2167-4031-9eb2-d9d38820099a · outbound

This paper cites Rapid and Noninvasive Sensory Analyses of Food Products by Hyperspectral Imaging: Recent Application Developments.Trends in Food Science & Technology, 111:151–165, 2021.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Rapid and Noninvasive Sensory Analyses of Food Products by Hyperspectral Imaging: Recent Application Developments.Trends in Food Science & Technology, 111:151–165, 2021

Reference 5

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.532652Z

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.

Observation 78ed46bb-5151-433a-bc36-cf8aae0a097b · outbound

This paper cites Frequency of Metamerism in Natural Scenes.Journal of the Optical Society of America A, 23(10):2359–2372, 2006.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Frequency of Metamerism in Natural Scenes.Journal of the Optical Society of America A, 23(10):2359–2372, 2006

Reference 6

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.520895Z

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.

Observation 7ddbd81d-495f-4512-b1ad-b6d2394c2eaa · outbound

This paper cites Victoria Martínez, Unai Martinez-Corral, Óscar Mata- Carballeira, and Inés del Campo.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Victoria Martínez, Unai Martinez-Corral, Óscar Mata- Carballeira, and Inés del Campo

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.098244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20cff0e6-fd9d-4481-872a-d8abf9660587 · outbound

This paper cites Hyper-Drive: Visible-Short Wave Infrared Hyperspectral Imaging Datasets for Robots in Unstructured Environments.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Hyper-Drive: Visible-Short Wave Infrared Hyperspectral Imaging Datasets for Robots in Unstructured Environments

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.101561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85921602-27ce-4b45-98a1-101dce4c52a3 · outbound

This paper cites Point-Supervised Semantic Segmentation of Natural Scenes via Hyperspectral Imaging.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Point-Supervised Semantic Segmentation of Natural Scenes via Hyperspectral Imaging

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.104535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83178464-7b1e-47c4-968d-041a333faf9c · outbound

This paper cites A Tiny VIS-NIR Snapshot Multi- spectral Camera.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach A Tiny VIS-NIR Snapshot Multi- spectral Camera

Reference 10

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.509684Z

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.

Observation 9737b362-b528-4888-adea-a0589d4bc0a1 · outbound

This paper cites Accurate Video-Rate Multi-Spectral Imaging Using IMEC Snapshot Sensors.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Accurate Video-Rate Multi-Spectral Imaging Using IMEC Snapshot Sensors

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.110795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a210f2f-cadb-4984-9f8f-6163de9b56ee · outbound

This paper cites A Compact Snapshot Multispectral Imager with A Monolithically Integrated Per-pixel Filter Mosaic.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach A Compact Snapshot Multispectral Imager with A Monolithically Integrated Per-pixel Filter Mosaic

Reference 12

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.498934Z

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.

Observation 9a1e81d2-f920-4ddf-a09a-0c12b3f38b7e · outbound

This paper cites Kria K26 SOM: The Ideal Platform for Vision AI at the Edge.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Kria K26 SOM: The Ideal Platform for Vision AI at the Edge

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:17.440467Z

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.

Observation 06c0a0a3-041e-4b19-9eee-3fbd7fdb54c9 · outbound

This paper cites Kria K26 SOM Data Sheet (DS987).

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Kria K26 SOM Data Sheet (DS987)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:17.211662Z

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.

Observation 3d2ce04b-2148-4c57-a5c0-126359ecf150 · outbound

This paper cites Arm Cortex-A53 MPCore Processor Technical Reference Manual.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Arm Cortex-A53 MPCore Processor Technical Reference Manual

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:17.005016Z

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.

Observation 909cb009-0c38-4fa4-a655-696778393ed1 · outbound

This paper cites DPUCZDX8G for Zynq UltraScale+ MPSoCs Product Guide (PG338).

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach DPUCZDX8G for Zynq UltraScale+ MPSoCs Product Guide (PG338)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.795644Z

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.

Observation 6e90d8db-0dbb-41e3-8b58-24e9b77cbd5c · outbound

This paper cites HSI-Drive v2.0: More Data for New Challenges in Scene Understanding for Autonomous Driving.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach HSI-Drive v2.0: More Data for New Challenges in Scene Understanding for Autonomous Driving

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.129409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d181b7b4-b8d0-4bcb-970a-6e57012b292a · outbound

This paper cites Hsi -drive, 2023.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Hsi -drive, 2023

Reference 18

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.488233Z

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.

Observation 8a62ba84-d649-41d4-96aa-152f84f6ccad · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmenta- tion.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach U-Net: Convolutional Networks for Biomedical Image Segmenta- tion

Reference 19

Resolution: malformed identifier; no resolver link, observed 2026-08-06T15:13:14.135715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 148bf7dd-7e50-43f3-94f9-ec739086b694 · outbound

This paper cites HyKo: A Spectral Dataset for Scene Understanding.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach HyKo: A Spectral Dataset for Scene Understanding

Reference 20

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.468450Z

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.

Observation 2a1ee968-ac7b-4e1a-a323-ba348a0fd283 · outbound

This paper cites HS3-Bench: A Benchmark and Strong Baseline for Hyperspectral Semantic Segmentation in Driving Scenarios.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach HS3-Bench: A Benchmark and Strong Baseline for Hyperspectral Semantic Segmentation in Driving Scenarios

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.141676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16cad89a-6744-45f6-a779-b61ac4f899f8 · outbound

This paper cites Hyperspectral City V1.0 Dataset and Benchmark.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Hyperspectral City V1.0 Dataset and Benchmark

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.144639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24e14be1-2695-4a4f-ab07-fa220b004df7 · outbound

This paper cites HSICityV2: Urban Scene Understanding via Hyper- spectral Images, Jul 2021.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach HSICityV2: Urban Scene Understanding via Hyper- spectral Images, Jul 2021

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.614508Z

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.

Observation 753927a7-cfb4-49c0-899e-66f7902edad8 · outbound

This paper cites Hsi Road: A Hyper Spectral Image Dataset for Road Segmentation.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Hsi Road: A Hyper Spectral Image Dataset for Road Segmentation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.535967Z

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.

Observation a7099078-e6e4-4ed1-bfcb-65d1f145a4bc · outbound

This paper cites Basterretxea, V.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Basterretxea, V

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.157069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37b9b1e8-787a-4d93-95a3-2a9194c4277e · outbound

This paper cites The Cityscapes Dataset for Semantic Urban Scene Understanding.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach The Cityscapes Dataset for Semantic Urban Scene Understanding

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.159987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cde09e49-8b9c-4e40-8cd9-79ed291d827e · outbound

This paper cites Semantic Object Classes in Video: A High-definition Ground Truth Database.Pattern Recognition Letters, 30(2):88–97, 2009.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Semantic Object Classes in Video: A High-definition Ground Truth Database.Pattern Recognition Letters, 30(2):88–97, 2009

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.167146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df1fe493-62db-46d5-9495-f733409e266e · outbound

This paper cites The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.170348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e4c2ea5-00fd-4dcc-b70b-2d980c5d12d8 · outbound

This paper cites The ApolloScape Dataset for Autonomous Driving.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach The ApolloScape Dataset for Autonomous Driving

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.173657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2464677c-99c3-4383-9530-199cace7e776 · outbound

This paper cites Cityscapes Dataset Benchmarks, 2024.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Cityscapes Dataset Benchmarks, 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.506396Z

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.

Observation e6c242a9-b89f-47e6-935e-70825f3efa12 · outbound

This paper cites Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.183305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7abbf60e-383d-4f25-bbda-c93110c6dbfa · outbound

This paper cites To prune, or not to prune: exploring the efficacy of pruning for model compression.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.186936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 674e16a2-736d-47cd-84b4-86ec8becb1c4 · outbound

This paper cites A Dynamic CNN Pruning Method Based on Matrix Similarity.Signal, Image and Video Processing, 15:381–389, 2021.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach A Dynamic CNN Pruning Method Based on Matrix Similarity.Signal, Image and Video Processing, 15:381–389, 2021

Reference 35

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.403121Z

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.

Observation 8ae42d5b-0105-43fd-8672-c377f441c9dc · outbound

This paper cites Importance Estimation for Neural Network Pruning.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Importance Estimation for Neural Network Pruning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.193981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71adbdf4-2951-4e7e-a10a-30103efd863d · outbound

This paper cites Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.474730Z

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.

Observation a1f173af-bec9-44f0-ba39-03a1f1b26950 · outbound

This paper cites A Fast Post- Training Pruning Framework for Transformers.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach A Fast Post- Training Pruning Framework for Transformers

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.448730Z

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.

Observation b4055a28-030f-48c8-be5c-6dc669222b25 · outbound

This paper cites Plug-and-play: An Efficient Post-training Pruning Method for Large Language Models.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Plug-and-play: An Efficient Post-training Pruning Method for Large Language Models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.418914Z

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.

Observation 412bfde3-4d90-412e-bfce-28dd00268b90 · outbound

This paper cites The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.205998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56070209-63d4-4471-9dc5-22c2e6d2eeac · outbound

This paper cites Rethinking the Value of Network Pruning.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Rethinking the Value of Network Pruning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.209602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 516c49fb-bf47-44a5-8a72-fb278a5db246 · outbound

This paper cites Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask.Advances in Neural Information Processing Systems, 32, 2019.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Deconstructing Lottery Tickets: Zeros, Signs, and the Supermask.Advances in Neural Information Processing Systems, 32, 2019

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.395302Z

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.

Observation d726992f-245f-4f8a-acf6-de610f833d6e · outbound

This paper cites What’s Hidden in A Randomly Weighted Neural Network? InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 11893–11902, 2020.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach What’s Hidden in A Randomly Weighted Neural Network? InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 11893–11902, 2020

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.216742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4174bbfe-173b-45ee-9b3a-212a2b382c4d · outbound

This paper cites Proving the Lottery Ticket Hypothesis: Pruning is All You Need.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Proving the Lottery Ticket Hypothesis: Pruning is All You Need

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.382231Z

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.

Observation 4cf42092-0efe-462e-baf1-7b5ed8cd280d · outbound

This paper cites A Comprehensive Review of Network Pruning Based on Pruning Granularity and Pruning Time Perspectives.Neurocomputing, page 129382, 2025.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach A Comprehensive Review of Network Pruning Based on Pruning Granularity and Pruning Time Perspectives.Neurocomputing, page 129382, 2025

Reference 45

Resolution: malformed identifier; no resolver link, observed 2026-08-06T15:13:14.223002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47e5347c-5f3b-454c-83be-64c97e87e392 · outbound

This paper cites A Survey on Deep Neural Network Pruning: Taxonomy, Comparison, Analysis, and Recommendations.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach A Survey on Deep Neural Network Pruning: Taxonomy, Comparison, Analysis, and Recommendations.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.226087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3676f5fa-e319-4d61-ae51-38a59e9cc434 · outbound

This paper cites Auto-compressing Subset Pruning for Semantic Image Segmentation.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Auto-compressing Subset Pruning for Semantic Image Segmentation

Reference 47

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.368598Z

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.

Observation 6269f25f-751d-4c33-a48c-22d0f02abed6 · outbound

This paper cites Finding Lottery Tickets in Vision Models via Data-driven Spectral Foresight Pruning.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Finding Lottery Tickets in Vision Models via Data-driven Spectral Foresight Pruning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.232866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91cbd62b-12a7-4414-8fa7-c4531c36ac69 · outbound

This paper cites STAMP: Simultaneous Training and Model Pruning for Low Data Regimes in Medical Image Segmentation.Medical Image Analysis, 81:102583, 2022.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach STAMP: Simultaneous Training and Model Pruning for Low Data Regimes in Medical Image Segmentation.Medical Image Analysis, 81:102583, 2022

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.236674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a91d6c53-c300-4d02-9c57-0a395dd38f61 · outbound

This paper cites Dynamically Pruning Segformer for Efficient Semantic Segmentation.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Dynamically Pruning Segformer for Efficient Semantic Segmentation

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.240128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 336fd1e4-4daa-4800-81bd-56d719d25b32 · outbound

This paper cites Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.243895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51e0add8-114c-4d7c-8185-55e3b1adaef4 · outbound

This paper cites Evaluating Single Event Upsets in Deep Neural Networks for Semantic Segmentation: An Embedded System Perspective.Journal of Systems Architecture, 154:103242,.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Evaluating Single Event Upsets in Deep Neural Networks for Semantic Segmentation: An Embedded System Perspective.Journal of Systems Architecture, 154:103242,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.371145Z

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.

Observation 5ac01a1d-3b6b-4465-bd73-4b94147789ee · outbound

This paper cites Victoria Martínez.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Victoria Martínez

Reference 53

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T15:13:14.829965Z

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.

Observation 9efcb138-c75c-4cfa-abc9-6527ebbc7436 · outbound

This paper cites Learn the Architecture: Introducing Neon.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Learn the Architecture: Introducing Neon

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.358199Z

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.

Observation 0f38aee5-9502-4576-9791-5f18ec6168bb · outbound

This paper cites Deep Learning with INT8 Optimization on Xilinx Devices.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Deep Learning with INT8 Optimization on Xilinx Devices

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.335717Z

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.

Observation 6a2b3c5c-fa9c-4242-b095-9860c5407384 · outbound

This paper cites Shift: A Zero Flop, Zero Parameter Alternative to Spatial Convolutions.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Shift: A Zero Flop, Zero Parameter Alternative to Spatial Convolutions

Reference 56

Resolution: verified exact; raw_fallback, observed 2026-08-06T15:13:14.704509Z

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.

Observation 58f3a6b0-5744-4ef3-8d79-1c37ce3a422b · outbound

This paper cites an unresolved cited work.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Unresolved cited work

Reference 57

Resolution: unresolved; raw_fallback, observed 2026-08-06T15:13:16.347024Z

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.

Observation 7f902cdc-40e2-4f84-87e3-7d9f96e0c410 · outbound

This paper cites Pruning Filters for Efficient ConvNets, 2017.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Pruning Filters for Efficient ConvNets, 2017

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.314564Z

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.

Observation a6d32e75-0fd5-4fa8-ba7f-a10ad9bf64fd · outbound

This paper cites Vitis AI User Guide.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Vitis AI User Guide

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.303115Z

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.

Observation cd27780c-3ff1-4da2-b167-0398a5a9b6a2 · outbound

This paper cites Optimal Brain Damage.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Optimal Brain Damage

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.325267Z

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.

Observation fbad68dd-335a-45f7-898c-a619dc02f81f · outbound

This paper cites Encoder-decoder with Atrous Separable Convolution for Semantic Image Segmentation.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Encoder-decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.279884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 600d085b-4361-40a3-856e-5793ada6ee79 · outbound

This paper cites OpenMP: An Industry Standard API for Shared-memory Programming.IEEE Computational Science and Engineering, 5(1):46–55, 1998.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach OpenMP: An Industry Standard API for Shared-memory Programming.IEEE Computational Science and Engineering, 5(1):46–55, 1998

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.282837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 817e4909-f1dc-4033-a0f4-bcd79124fd1e · outbound

This paper cites Real-time Semantic Image Segmentation with Deep Learning for Autonomous Driving: A Survey.Applied Sciences, 11(19):8802, 2021.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Real-time Semantic Image Segmentation with Deep Learning for Autonomous Driving: A Survey.Applied Sciences, 11(19):8802, 2021

Reference 63

Resolution: verified exact; doi, observed 2026-08-06T15:13:14.342596Z

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.

Observation 353d1ebb-e474-4278-bdaf-5d2d58c08217 · outbound

This paper cites Addison-Wesley Professional, 1997.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Addison-Wesley Professional, 1997

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:13:16.289018Z

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.

Observation b1960595-db74-40ea-b561-0c5fdd7ef321 · outbound

This paper cites an unresolved cited work.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Unresolved cited work

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.154280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7022af19-be95-4c6d-acd1-25e945c021c2 · outbound

This paper cites an unresolved cited work.

Optimization of DNN-based HSI Segmentation FPGA-based SoC for ADS: A Practical Approach Unresolved cited work

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T15:13:14.250228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers