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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

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

Reference 41

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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 2026-08-11T06:34:44.6726+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.

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Reference resolution

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