Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Deora, Puneesh"'
Self-attention, the core mechanism of transformers, distinguishes them from traditional neural networks and drives their outstanding performance. Towards developing the fundamental optimization principles of self-attention, we investigate the implici
Externí odkaz:
http://arxiv.org/abs/2402.05738
The training and generalization dynamics of the Transformer's core mechanism, namely the Attention mechanism, remain under-explored. Besides, existing analyses primarily focus on single-head attention. Inspired by the demonstrated benefits of overpar
Externí odkaz:
http://arxiv.org/abs/2310.12680
Deep metric learning has been effectively used to learn distance metrics for different visual tasks like image retrieval, clustering, etc. In order to aid the training process, existing methods either use a hard mining strategy to extract the most in
Externí odkaz:
http://arxiv.org/abs/2108.09335
Autor:
Ignatov, Andrey, Timofte, Radu, Zhang, Zhilu, Liu, Ming, Wang, Haolin, Zuo, Wangmeng, Zhang, Jiawei, Zhang, Ruimao, Peng, Zhanglin, Ren, Sijie, Dai, Linhui, Liu, Xiaohong, Li, Chengqi, Chen, Jun, Ito, Yuichi, Vasudeva, Bhavya, Deora, Puneesh, Pal, Umapada, Guo, Zhenyu, Zhu, Yu, Liang, Tian, Li, Chenghua, Leng, Cong, Pan, Zhihong, Li, Baopu, Kim, Byung-Hoon, Song, Joonyoung, Ye, Jong Chul, Baek, JaeHyun, Zhussip, Magauiya, Koishekenov, Yeskendir, Ye, Hwechul Cho, Liu, Xin, Hu, Xueying, Jiang, Jun, Gu, Jinwei, Li, Kai, Tan, Pengliang, Hou, Bingxin
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to-RGB mapping problem, where to goal was to map the original low-qualit
Externí odkaz:
http://arxiv.org/abs/2011.04994
Compressive sensing (CS) is widely used to reduce the acquisition time of magnetic resonance imaging (MRI). Although state-of-the-art deep learning based methods have been able to obtain fast, high-quality reconstruction of CS-MR images, their main d
Externí odkaz:
http://arxiv.org/abs/2002.10523
Compressive sensing magnetic resonance imaging (CS-MRI) accelerates the acquisition of MR images by breaking the Nyquist sampling limit. In this work, a novel generative adversarial network (GAN) based framework for CS-MRI reconstruction is proposed.
Externí odkaz:
http://arxiv.org/abs/1910.06067
In this paper, the field programmable gate array (FPGA) implementation of a fetal heart rate (FHR) monitoring system is presented. The system comprises of a preprocessing unit to remove various types of noise, followed by a fetal electrocardiogram (F
Externí odkaz:
http://arxiv.org/abs/1910.07496
Publikováno v:
Healthcare Technology Letters; 2020, Vol. 7 Issue 5, p125-131, 7p