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Feature extraction, Semantics, Decoding, Transformers, Convolution,
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Zhong, B.[Bo],
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Transformers, Task analysis, Object detection,
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Shifted Windows.
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biomedical magnetic resonance imaging, image segmentation,
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Costs, Computational modeling, Graphics processing units,
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Energy consumption, Adaptation models,
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Ning, J.[Jia],
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BRAVO23(4032-4041)
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ICCV23(5906-5915)
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Liu, Z.[Ze],
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Cao, Y.[Yue],
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Award, Marr Prize. Image segmentation, Visualization, Computational modeling,
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Swin-Transformer-Object-Detection,
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Ling, Z.X.[Zhi-Xin],
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PanoSwin: a Pano-style Swin Transformer for Panorama Understanding,
CVPR23(17755-17764)
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2309
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Wang, Y.X.[Yan-Xue],
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An Instance Segmentation Method for Anthracnose Based on Swin
Transformer and Path Aggregation,
ICIVC22(381-386)
IEEE DOI
2301
Image segmentation, Shape, Transfer learning, Crops, Transformers,
Feature extraction, Lesions, Swin Transformer, PANet, anthracnose,
instance segmentation
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Li, B.C.[Bing-Chen],
Li, X.[Xin],
Lu, Y.T.[Yi-Ting],
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HST: Hierarchical Swin Transformer for Compressed Image
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Springer DOI
2304
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Conde, M.V.[Marcos V.],
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Swin2sr: Swinv2 Transformer for Compressed Image Super-resolution and
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Liu, Z.[Ze],
Hu, H.[Han],
Lin, Y.T.[Yu-Tong],
Yao, Z.L.[Zhu-Liang],
Xie, Z.D.[Zhen-Da],
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Ning, J.[Jia],
Cao, Y.[Yue],
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Dong, L.[Li],
Wei, F.[Furu],
Guo, B.[Baining],
Swin Transformer V2: Scaling Up Capacity and Resolution,
CVPR22(11999-12009)
IEEE DOI
2210
Training, Representation learning, Adaptation models,
Image resolution, Computational modeling, Semantics,
Representation learning
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Dong, X.Y.[Xiao-Yi],
Bao, J.M.[Jian-Min],
Chen, D.D.[Dong-Dong],
Zhang, W.M.[Wei-Ming],
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Yuan, L.[Lu],
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CSWin Transformer: A General Vision Transformer Backbone with
Cross-Shaped Windows,
CVPR22(12114-12124)
IEEE DOI
2210
Image segmentation, Costs, Mathematical analysis, Training data,
Transformer cores, Transformers,
grouping and shape analysis
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Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Semi-Supervised Object Detection .