Now showing items 1-3 of 3

    • Enhancing few-shot image classification with cosine transformer 

      Nguyen, Quang Huy; Nguyen, Q. Cuong; Le, D. Dung; Pham, H. Hieu (2023-07-21)
      This paper addresses the few-shot image classification problem, where the classification task is performed on unlabeled query samples given a small amount of labeled support samples only. One major challenge of the few-shot ...
    • Improving transformers with probabilistic attention keys 

      Nguyen, Tam; Nguyen, M. Tan; Le, D. Dung; Nguyen, Khuong Duy; Tran, Viet Anh; Baraniuk, Richard G.; Osher, Stanley J.; Ho, Nhat (2022-06-13)
      Multi-head attention is a driving force behind state-of-the-art transformers, which achieve remarkable performance across a variety of natural language processing (NLP) and computer vision tasks. It has been observed that ...
    • VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations 

      Nguyen, Ha Q.; Lam, Khanh; Le, T. Linh; Pham, H. Hieu; Tran, Q. Dat; Nguyen, B. Dung; Le, D. Dung; Tong, T. T. Hang; Dinh, H. Hiep; Do, D. Cuong; Doan, T. Luu; Nguyen, N. Cuong; Nguyen, T. Binh; Nguyen, V. Que; Hoang, D. Au; Phan, N. Hien; Nguyen, T. Anh; Ho, H. Phuong; Ngo, T. Dat; Nguyen, T. Nghia; Nguyen, T. Nhan; Dao, Minh; Vu, Van (2022-03-20)
      Most of the existing chest X-ray datasets include labels from a list of findings without specifying their locations on the radiographs. This limits the development of machine learning algorithms for the detection and ...

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