no code implementations • 18 Apr 2023 • Ping Gong, Yuxin Ma, Cheng Li, Xiaosong Ma, Sam H. Noh
In this paper, we primarily focus on understanding the data preprocessing pipeline for DNN Training in the public cloud.
no code implementations • 11 Oct 2022 • Zong Fan, Ping Gong, Shanshan Tang, Christine U. Lee, Xiaohui Zhang, Pengfei Song, Shigao Chen, Hua Li
By use of the attention mechanism, the auxiliary lesion-aware network can optimize multi-scale intermediate feature maps and extract rich semantic information to improve classification and localization performance.
no code implementations • 31 Jul 2022 • Zihao Yin, Ping Gong, Chunyu Wang, Yizhou Yu, Yizhou Wang
As an important upstream task for many medical applications, supervised landmark localization still requires non-negligible annotation costs to achieve desirable performance.
1 code implementation • 29 Jul 2022 • Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao, Cheng Li, Yuxiong He, Feng Yan
We identify the main accuracy impact factors in graph feature quantization and theoretically prove that BiFeat training converges to a network where the loss is within $\epsilon$ of the optimal loss of uncompressed network.
no code implementations • 3 Mar 2021 • Ping Gong, Wenwen Yu, Qiuwen Sun, Ruohan Zhao, Junfeng Hu
Specifically, our approach consists of two key modules, a conditional domain discriminator~(CDD) and a category-centric prototype aligner~(CCPA).
2 code implementations • 16 Apr 2020 • Wenwen Yu, Ning Lu, Xianbiao Qi, Ping Gong, Rong Xiao
Computer vision with state-of-the-art deep learning models has achieved huge success in the field of Optical Character Recognition (OCR) including text detection and recognition tasks recently.
7 code implementations • 7 Oct 2019 • Ning Lu, Wenwen Yu, Xianbiao Qi, Yihao Chen, Ping Gong, Rong Xiao, Xiang Bai
Attention-based scene text recognizers have gained huge success, which leverages a more compact intermediate representation to learn 1d- or 2d- attention by a RNN-based encoder-decoder architecture.