no code implementations • 2 Jun 2015 • Xiangyu Zeng, Shi Yin, Dong Wang
A significant performance reduction is often observed in speech recognition when the rate of speech (ROS) is too low or too high.
no code implementations • 28 Aug 2018 • Shi Yin, Yi Zhou, Chenguang Li, Shangfei Wang, Jianmin Ji, Xiaoping Chen, Ruili Wang
We propose KDSL, a new word sense disambiguation (WSD) framework that utilizes knowledge to automatically generate sense-labeled data for supervised learning.
no code implementations • 12 Nov 2018 • Shi Yin, Qinmu Peng, Hongming Li, Zhengqiang Zhang, Xinge You, Susan L. Furth, Gregory E. Tasian, Yong Fan
It remains challenging to automatically segment kidneys in clinical ultrasound (US) images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic methods have achieved promising performance.
no code implementations • 5 Jan 2019 • Shi Yin, Zhengqiang Zhang, Hongming Li, Qinmu Peng, Xinge You, Susan L. Furth, Gregory E. Tasian, Yong Fan
It remains challenging to automatically segment kidneys in clinical ultrasound images due to the kidneys' varied shapes and image intensity distributions, although semi-automatic methods have achieved promising performance.
no code implementations • 21 Mar 2019 • Shi Yin, Zhengqiang Zhang, Qinmu Peng, Xinge You
High angular resolution diffusion imaging (HARDI) demands a lager amount of data measurements compared to diffusion tensor imaging, restricting its use in practice.
no code implementations • 29 May 2019 • Zhengqiang Zhang, Shujian Yu, Shi Yin, Qinmu Peng, Xinge You
Weakly-supervised semantic segmentation aims to assign each pixel a semantic category under weak supervisions, such as image-level tags.
no code implementations • 18 Nov 2019 • Shangfei Wang, Shi Yin, Longfei Hao, Guang Liang
Through multi-task learning mechanism, the recognition network explores the dependencies among multiple face analysis tasks, such as facial landmark localization, head pose estimation, gender recognition and face attribute estimation from image representation-level.
no code implementations • 5 Apr 2020 • Shi Yin, Shangfei Wang, Xiaoping Chen, Enhong Chen
These 1D heatmaps reduce spatial complexity significantly compared to current heatmap regression methods, which use 2D heatmaps to represent the joint distributions of x and y coordinates.
no code implementations • 28 May 2023 • Ying Shi, Dong Wang, Lantian Li, Jiqing Han, Shi Yin
We propose a novel Mix Training (MT) strategy that encourages the model to discover low-energy keywords from noisy and mixed speech.
no code implementations • 1 Nov 2023 • Shi Yin, Shijie Huan, Shangfei Wang, Jinshui Hu, Tao Guo, Bing Yin, BaoCai Yin, Cong Liu
For temporal modeling, we propose a recurrent token mixing mechanism, an axis-landmark-positional embedding mechanism, as well as a confidence-enhanced multi-head attention mechanism to adaptively and robustly embed long-term landmark dynamics into their 1D representations; for structure modeling, we design intra-group and inter-group structure modeling mechanisms to encode the component-level as well as global-level facial structure patterns as a refinement for the 1D representations of landmarks through token communications in the spatial dimension via 1D convolutional layers.
no code implementations • 1 Jan 2024 • Shi Yin, Xinyang Pan, XUDONG ZHU, Tianyu Gao, Haochong Zhang, Feng Wu, Lixin He
Deep learning for Hamiltonian regression of quantum systems in material research necessitates satisfying the covariance laws, among which achieving SO(3)-equivariance without sacrificing the expressiveness capability of networks remains unsolved due to the restriction on non-linear mappings in assuring theoretical equivariance.