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Review the state-of-the-art technologies of semantic segmentation based on deep learning

Neurocomputing · 2022 · Vol. 493 · pp. 626–646
Yujian MoYan WuXinneng YangFeilin LiuYujun Liao
Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot LearningMultimodal Machine Learning ApplicationsComputer scienceSegmentationArtificial intelligenceSegmentation-based object categorizationScale-space segmentationSemantic computingDeep learningMachine learningImage segmentationPattern recognition (psychology)

Funding

  • National Natural Science Foundation of China
Citations
596
FWCI
57.97
field-weighted impact
References
191
Percentile
100%
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Citations per year
References
Fully Convolutional Networks for Semantic Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2016 · 10,957 citations
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2017 · 21,645 citations
Semantic Understanding of Scenes Through the ADE20K Dataset
International Journal of Computer Vision · 2018 · 1,599 citations
ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation
IEEE Transactions on Intelligent Transportation Systems · 2017 · 1,469 citations
Deep visual domain adaptation: A survey
Neurocomputing · 2018 · 2,125 citations
Squeeze-and-Excitation Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence · 2019 · 12,333 citations
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
IEEE Transactions on Medical Imaging · 2019 · 3,913 citations
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