no code implementations • NeurIPS Workshop ICBINB 2021 • Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya, Umapada Pal, Sukalpa Chanda
Deep metric learning (ML) uses a carefully designed loss function to learn distance metrics for improving the discriminatory ability for tasks like clustering and retrieval.
1 code implementation • ICCV 2021 • Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya, Umapada Pal, Sukalpa Chanda
Deep metric learning has been effectively used to learn distance metrics for different visual tasks like image retrieval, clustering, etc.
no code implementations • 20 Feb 2021 • Bhavya Vasudeva, Runfeng Tian, Dee H. Wu, Shirley A. James, Hazem H. Refai, Fei He, Yuan Yang
Methods such as $n:m$ phase locking value and bi-phase locking value have previously been proposed to quantify phase coupling between two resonant frequencies (e. g. $f$, $2f/3$) and across three frequencies (e. g. $f_1$, $f_2$, $f_1+f_2$), respectively.
1 code implementation • 10 Nov 2020 • Andrey Ignatov, Radu Timofte, Zhilu Zhang, Ming Liu, Haolin Wang, WangMeng Zuo, Jiawei Zhang, Ruimao Zhang, Zhanglin Peng, Sijie Ren, Linhui Dai, Xiaohong Liu, Chengqi Li, Jun Chen, Yuichi Ito, Bhavya Vasudeva, Puneesh Deora, Umapada Pal, Zhenyu Guo, Yu Zhu, Tian Liang, Chenghua Li, Cong Leng, Zhihong Pan, Baopu Li, Byung-Hoon Kim, Joonyoung Song, Jong Chul Ye, JaeHyun Baek, Magauiya Zhussip, Yeskendir Koishekenov, Hwechul Cho Ye, Xin Liu, Xueying Hu, Jun Jiang, Jinwei Gu, Kai Li, Pengliang Tan, Bingxin Hou
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results.
no code implementations • 24 Feb 2020 • Bhavya Vasudeva, Puneesh Deora, Saumik Bhattacharya, Pyari Mohan Pradhan
Although state-of-the-art deep learning based methods have been able to obtain fast, high-quality reconstruction of CS-MR images, their main drawback is that they treat complex-valued MRI data as real-valued entities.
1 code implementation • 14 Oct 2019 • Puneesh Deora, Bhavya Vasudeva, Saumik Bhattacharya, Pyari Mohan Pradhan
Compressive sensing magnetic resonance imaging (CS-MRI) accelerates the acquisition of MR images by breaking the Nyquist sampling limit.