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Darksegnet: Low-Light Semantic Segmentation Network Based on Image Pyramid

https://doi.org/10.2139/ssrn.4686176
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inferredcites →https://doi.org/10.1007/978-3-030-01228-1_26openalex-extracted
Unified Perceptual Parsing for Scene Understanding
inferredcites →https://doi.org/10.1007/978-3-030-01234-2_49openalex-extracted
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-031-44195-0_14openalex-extracted
PE-YOLO: Pyramid Enhancement Network for Dark Object Detection
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-extracted
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/s11263-011-0444-0openalex-extracted
Segmentation of Natural Images by Texture and Boundary Compression
inferredcites →https://doi.org/10.1007/s11370-019-00287-6openalex-extracted
Autonomous robot navigation using Retinex algorithm for multiscale image adaptability in low-light environment
inferredcites →https://doi.org/10.1016/b978-0-08-051581-6.50065-9openalex-extracted
The Laplacian Pyramid as a Compact Image Code
inferredcites →https://doi.org/10.1016/j.isprsjprs.2021.11.010openalex-extracted
LISU: Low-light indoor scene understanding with joint learning of reflectance restoration
inferredcites →https://doi.org/10.1016/j.neucom.2019.11.118openalex-extracted
A Brief Survey on Semantic Segmentation with Deep Learning
inferredcites →https://doi.org/10.1088/1742-6596/1755/1/012006openalex-extracted
Face Recognition and Identification using Deep Learning Approach
inferredcites →https://doi.org/10.1109/cvpr.2015.7298965openalex-extracted
Fully convolutional networks for semantic segmentation
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-extracted
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-extracted
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.549openalex-extracted
RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.634openalex-extracted
Aggregated Residual Transformations for Deep Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2017.660openalex-extracted
Pyramid Scene Parsing Network
inferredcites →https://doi.org/10.1109/cvpr.2019.00326openalex-extracted
Dual Attention Network for Scene Segmentation
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00185openalex-extracted
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00681openalex-extracted
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01551openalex-extracted
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01643openalex-extracted
NightLab: A Dual-level Architecture with Hardness Detection for Segmentation at Night
inferredcites →https://doi.org/10.1109/icce-asia49877.2020.9277442openalex-extracted
Low-Light Image Enhancement for Autonomous Driving Systems using DriveRetinex-Net
inferredcites →https://doi.org/10.1109/iccvw.2019.00293openalex-extracted
FuseMODNet: Real-Time Camera and LiDAR Based Moving Object Detection for Robust Low-Light Autonomous Driving
inferredcites →https://doi.org/10.1109/icdmw.2018.00176openalex-extracted
A Survey on Semantic Segmentation
inferredcites →https://doi.org/10.1109/itsc.2019.8917151openalex-extracted
Coarse-to-Fine Luminance Estimation for Low-Light Image Enhancement in Maritime Video Surveillance
inferredcites →https://doi.org/10.1109/tcsvt.2023.3260240openalex-extracted
Improving Nighttime Driving-Scene Segmentation via Dual Image-Adaptive Learnable Filters
inferredcites →https://doi.org/10.1109/tip.2021.3051462openalex-extracted
EnlightenGAN: Deep Light Enhancement Without Paired Supervision
inferredcites →https://doi.org/10.1109/tip.2021.3122004openalex-extracted
Night-Time Scene Parsing With a Large Real Dataset
inferredcites →https://doi.org/10.1109/tpami.2016.2644615openalex-extracted
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
inferredcites →https://doi.org/10.1109/tpami.2017.2699184openalex-extracted
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
inferredcites →https://doi.org/10.1145/1553374.1553479openalex-extracted
Multi-class image segmentation using conditional random fields and global classification
inferredcites →https://doi.org/10.1145/2010324.1964963openalex-extracted
Local Laplacian filters
inferredcites →https://doi.org/10.1145/3343031.3350926openalex-extracted
Kindling the Darkness
inferredcites →https://doi.org/10.1186/s40064-015-1226-xopenalex-extracted
Adaptively partitioned block-based contrast enhancement and its application to low light-level video surveillance
inferredcites →https://doi.org/10.1364/ao.486302openalex-extracted
ASA-BiSeNet: improved real-time approach for road lane semantic segmentation of low-light autonomous driving road scenes
inferredcites →https://doi.org/10.14257/ijsip.2015.8.8.35openalex-extracted
Histogram Equalization: A Strong Technique for Image Enhancement
inferredcites →https://doi.org/10.1609/aaai.v37i1.25126openalex-extracted
Head-Free Lightweight Semantic Segmentation with Linear Transformer
inferredcites →https://doi.org/10.3390/rs14030663openalex-extracted
A Precision Efficient Method for Collapsed Building Detection in Post-Earthquake UAV Images Based on the Improved NMS Algorithm and Faster R-CNN
inferredcites →https://doi.org/10.3390/rs15112870openalex-extracted
UAV, GNSS, and InSAR Data Analyses for Landslide Monitoring in a Mountainous Village in Western Greece
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-extracted
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.48550/arxiv.1411.4038openalex-extracted
Fully Convolutional Networks for Semantic Segmentation
inferredcites →https://doi.org/10.48550/arxiv.1412.7062openalex-extracted
Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
inferredcites →https://doi.org/10.48550/arxiv.1506.05751openalex-extracted
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
inferredcites →https://doi.org/10.48550/arxiv.1706.05587openalex-extracted
Rethinking Atrous Convolution for Semantic Image Segmentation
inferredcites →https://doi.org/10.48550/arxiv.1802.02611openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.1905.04161openalex-extracted
Kindling the Darkness: A Practical Low-light Image Enhancer
inferredcites →https://doi.org/10.48550/arxiv.2001.06826openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2010.11929openalex-extracted
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
inferredcites →https://doi.org/10.48550/arxiv.2012.15840openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2104.10834openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2105.15203openalex-extracted
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
inferredcites →https://doi.org/10.48550/arxiv.2204.05538openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2207.01331openalex-extracted
inferredcites →https://doi.org/10.7551/mitpress/8579.001.0001openalex-extracted
Markov Random Fields for Vision and Image Processing
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