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[1] Christoph Feichtenhofer,et al. Multiscale Vision Transformers , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[2] Yu-Gang Jiang,et al. M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection , 2021, ArXiv.
[3] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] Stephen Lin,et al. Swin Transformer: Hierarchical Vision Transformer using Shifted Windows , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[5] Nicolas Usunier,et al. End-to-End Object Detection with Transformers , 2020, ECCV.
[6] Yunchao Wei,et al. CCNet: Criss-Cross Attention for Semantic Segmentation , 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[7] Antonio M. López,et al. A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images , 2016, Journal of healthcare engineering.
[8] Jiashi Feng,et al. Coordinate Attention for Efficient Mobile Network Design , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Loïc Le Folgoc,et al. Attention U-Net: Learning Where to Look for the Pancreas , 2018, ArXiv.
[10] Lanfen Lin,et al. UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[11] Vishal M. Patel,et al. KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations , 2020, MICCAI.
[12] Harald Kittler,et al. Descriptor : The HAM 10000 dataset , a large collection of multi-source dermatoscopic images of common pigmented skin lesions , 2018 .
[13] Georg Heigold,et al. An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale , 2021, ICLR.
[14] Rogério Schmidt Feris,et al. A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection , 2016, ECCV.
[15] Sharib Ali,et al. Real-Time Polyp Detection, Localisation and Segmentation in Colonoscopy Using Deep Learning , 2020, ArXiv.
[16] Noel C. F. Codella,et al. Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC) , 2019, ArXiv.
[17] Cheng Chen,et al. Selective Feature Aggregation Network with Area-Boundary Constraints for Polyp Segmentation , 2019, MICCAI.
[18] Tae Hyun Kim,et al. Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[20] Kaiming He,et al. Feature Pyramid Networks for Object Detection , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[21] Yan Wang,et al. TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation , 2021, ArXiv.
[22] Quanfu Fan,et al. CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[23] Anne E Carpenter,et al. Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl , 2019, Nature Methods.
[24] Thomas de Lange,et al. Kvasir-SEG: A Segmented Polyp Dataset , 2019, MMM.
[25] Fernando Vilariño,et al. WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians , 2015, Comput. Medical Imaging Graph..
[26] Sharib Ali,et al. FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation , 2021, ArXiv.
[27] Youn-Long Lin,et al. HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS , 2021, ArXiv.
[28] Rogério Schmidt Feris,et al. Big-Little Net: An Efficient Multi-Scale Feature Representation for Visual and Speech Recognition , 2018, ICLR.
[29] Aymeric Histace,et al. Toward embedded detection of polyps in WCE images for early diagnosis of colorectal cancer , 2014, International Journal of Computer Assisted Radiology and Surgery.
[30] Matthieu Cord,et al. Training data-efficient image transformers & distillation through attention , 2020, ICML.
[31] Xiaogang Wang,et al. Pyramid Scene Parsing Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Abhinav Gupta,et al. Non-local Neural Networks , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[33] Mahmood Fathy,et al. Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions , 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).
[34] Zhiming Luo,et al. Weighted Res-UNet for High-Quality Retina Vessel Segmentation , 2018, 2018 9th International Conference on Information Technology in Medicine and Education (ITME).
[35] Michael A. Riegler,et al. DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation , 2020, 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS).
[36] Chi-Wing Fu,et al. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes , 2018, IEEE Transactions on Medical Imaging.
[37] Roberto Cipolla,et al. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[38] Ling Shao,et al. PraNet: Parallel Reverse Attention Network for Polyp Segmentation , 2020, MICCAI.
[39] Vishal M. Patel,et al. Medical Transformer: Gated Axial-Attention for Medical Image Segmentation , 2021, MICCAI.
[40] Tao Xiang,et al. Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers , 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[41] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[42] George Papandreou,et al. Rethinking Atrous Convolution for Semantic Image Segmentation , 2017, ArXiv.
[43] A. Yuille,et al. Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation , 2020, ECCV.
[44] Yang Zhao,et al. Deep High-Resolution Representation Learning for Visual Recognition , 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Qingjie Liu,et al. Road Extraction by Deep Residual U-Net , 2017, IEEE Geoscience and Remote Sensing Letters.
[46] Nima Tajbakhsh,et al. UNet++: A Nested U-Net Architecture for Medical Image Segmentation , 2018, DLMIA/ML-CDS@MICCAI.
[47] Nima Tajbakhsh,et al. Automated Polyp Detection in Colonoscopy Videos Using Shape and Context Information , 2016, IEEE Transactions on Medical Imaging.
[48] Huiye Liu,et al. TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation , 2021, MICCAI.
[49] Thomas de Lange,et al. ResUNet++: An Advanced Architecture for Medical Image Segmentation , 2019, 2019 IEEE International Symposium on Multimedia (ISM).
[50] Vijayan K. Asari,et al. Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation , 2018, ArXiv.
[51] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.