Search Results for author: Shi Yin

Found 11 papers, 0 papers with code

Learning Speech Rate in Speech Recognition

no code implementations2 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.

speech-recognition Speech Recognition

KDSL: a Knowledge-Driven Supervised Learning Framework for Word Sense Disambiguation

no code implementations28 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.

Word Sense Disambiguation

Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks

no code implementations12 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.

Classification Data Augmentation +3

Fully-automatic segmentation of kidneys in clinical ultrasound images using a boundary distance regression network

no code implementations5 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.

Classification Distance regression +2

Fast and accurate reconstruction of HARDI using a 1D encoder-decoder convolutional network

no code implementations21 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.

Closed-Loop Adaptation for Weakly-Supervised Semantic Segmentation

no code implementations29 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.

Segmentation Superpixels +2

Multiple Face Analyses through Adversarial Learning

no code implementations18 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.

Attribute Face Alignment +2

Attentive One-Dimensional Heatmap Regression for Facial Landmark Detection and Tracking

no code implementations5 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.

Face Alignment Facial Landmark Detection +3

Spot keywords from very noisy and mixed speech

no code implementations28 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.

Data Augmentation Keyword Spotting

1DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking

no code implementations1 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.

Landmark Tracking

Harmonizing Covariance and Expressiveness for Deep Hamiltonian Regression in Crystalline Material Research: a Hybrid Cascaded Regression Framework

no code implementations1 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.

regression

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