본문 바로가기

논문 리뷰

 (25)
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks 논문 리뷰 Lewis, Patrick, et al. "Retrieval-augmented generation for knowledge-intensive nlp tasks." Advances in Neural Information Processing Systems 33 (2020): 9459-9474.  Retrieval-Augmented Generation for Knowledge-Intensive NLP TasksRequests for name changes in the electronic proceedings will be accepted with no questions asked. However name changes may cause bibliographic tracking issues. Authors ar..
Adaptformer: Adapting vision transformers for scalable visual recognition 리뷰 Chen, Shoufa, Chongjian Ge, Zhan Tong, Jiangliu Wang, Yibing Song, Jue Wang, and Ping Luo. "Adaptformer: Adapting vision transformers for scalable visual recognition." Advances in Neural Information Processing Systems 35 (2022): 16664-16678.  AdaptFormer: Adapting Vision Transformers for Scalable Visual RecognitionRequests for name changes in the electronic proceedings will be accepted with no q..
Vision transformer adapter for dense predictions 리뷰 Chen, Zhe, Yuchen Duan, Wenhai Wang, Junjun He, Tong Lu, Jifeng Dai, and Yu Qiao. "Vision transformer adapter for dense predictions." arXiv preprint arXiv:2205.08534 (2022).  Vision Transformer Adapter for Dense PredictionsThis work investigates a simple yet powerful dense prediction task adapter for Vision Transformer (ViT). Unlike recently advanced variants that incorporate vision-specific ind..
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation 리뷰 Wu, Junde, Rao Fu, Huihui Fang, Yuanpei Liu, Zhaowei Wang, Yanwu Xu, Yueming Jin, and Tal Arbel. "Medical sam adapter: Adapting segment anything model for medical image segmentation." arXiv preprint arXiv:2304.12620 (2023).  Medical SAM Adapter: Adapting Segment Anything Model for Medical Image SegmentationThe Segment Anything Model (SAM) has recently gained popularity in the field of image segm..
MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model 리뷰 Wu, Junde, Rao Fu, Huihui Fang, Yu Zhang, Yehui Yang, Haoyi Xiong, Huiying Liu, and Yanwu Xu. "Medsegdiff: Medical image segmentation with diffusion probabilistic model." In Medical Imaging with Deep Learning, pp. 1623-1639. PMLR, 2024.  MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic ModelDiffusion Probabilistic Model (DPM) has recently become one of the hottest topics in co..
nnFormer: Volumetric Medical Image Segmentation via a 3D Transformer 리뷰 Zhou, Hong-Yu, Jiansen Guo, Yinghao Zhang, Xiaoguang Han, Lequan Yu, Liansheng Wang, and Yizhou Yu. "nnformer: Volumetric medical image segmentation via a 3d transformer." IEEE Transactions on Image Processing (2023).  nnFormer: Volumetric Medical Image Segmentation via a 3D TransformerTransformer, the model of choice for natural language processing, has drawn scant attention from the medical im..
The fully convolutional transformer for medical image segmentation 리뷰 Tragakis, Athanasios, Chaitanya Kaul, Roderick Murray-Smith, and Dirk Husmeier. "The fully convolutional transformer for medical image segmentation." In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 3660-3669. 2023. WACV 2023 Open Access Repository The Fully Convolutional Transformer for Medical Image Segmentation Athanasios Tragakis, Chaitanya Kaul, Roder..
Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation 리뷰 Cao, Hu, Yueyue Wang, Joy Chen, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian, and Manning Wang. "Swin-unet: Unet-like pure transformer for medical image segmentation." In European conference on computer vision, pp. 205-218. Cham: Springer Nature Switzerland, 2022. Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation In the past few years, convolutional neural networks (CNNs) have ach..

티스토리툴바