Search Results for author: Yemin Shi

Found 10 papers, 3 papers with code

Identification of Pediatric Respiratory Diseases Using Fine-grained Diagnosis System

no code implementations24 Aug 2021 Gang Yu, Zhongzhi Yu, Yemin Shi, Yingshuo Wang, Xiaoqing Liu, Zheming Li, Yonggen Zhao, Fenglei Sun, Yizhou Yu, Qiang Shu

The first stage structuralizes test results by extracting relevant numerical values from clinical notes, and the disease identification stage provides a diagnosis based on text-form clinical notes and the structured data obtained from the first stage.

Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation

1 code implementation CVPR 2021 Jichang Li, Guanbin Li, Yemin Shi, Yizhou Yu

Pseudo labeling expands the number of ``labeled" samples in each class in the target domain, and thus produces a more robust and powerful cluster core for each class to facilitate adversarial learning.

Domain Adaptation

Learning Open Set Network with Discriminative Reciprocal Points

1 code implementation ECCV 2020 Guangyao Chen, Limeng Qiao, Yemin Shi, Peixi Peng, Jia Li, Tiejun Huang, ShiLiang Pu, Yonghong Tian

In this process, one of the key challenges is to reduce the risk of generalizing the inherent characteristics of numerous unknown samples learned from a small amount of known data.

Open Set Learning

Kernel Quantization for Efficient Network Compression

no code implementations11 Mar 2020 Zhongzhi Yu, Yemin Shi, Tiejun Huang, Yizhou Yu

Thus, KQ can represent the weight tensor in the convolution layer with low-bit indexes and a kernel codebook with limited size, which enables KQ to achieve significant compression ratio.

Quantization

Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning

no code implementations ICCV 2019 Limeng Qiao, Yemin Shi, Jia Li, Yao-Wei Wang, Tiejun Huang, Yonghong Tian

By solving the problem with its closed-form solution on the fly with the setup of transduction, our approach efficiently tailors an episodic-wise metric for each task to adapt all features from a shared task-agnostic embedding space into a more discriminative task-specific metric space.

Few-Shot Learning Metric Learning

P-ODN: Prototype based Open Deep Network for Open Set Recognition

no code implementations6 May 2019 Yu Shu, Yemin Shi, Yao-Wei Wang, Tiejun Huang, Yonghong Tian

Predictors for new categories are added to the classification layer to "open" the deep neural networks to incorporate new categories dynamically.

Open Set Learning

ODN: Opening the Deep Network for Open-set Action Recognition

no code implementations23 Jan 2019 Yu Shu, Yemin Shi, Yao-Wei Wang, Yixiong Zou, Qingsheng Yuan, Yonghong Tian

Most of the existing action recognition works hold the \textit{closed-set} assumption that all action categories are known beforehand while deep networks can be well trained for these categories.

Open Set Action Recognition

Joint Network based Attention for Action Recognition

no code implementations16 Nov 2016 Yemin Shi, Yonghong Tian, Yao-Wei Wang, Tiejun Huang

We also introduce an attention mechanism on the temporal domain to capture the long-term dependence meanwhile finding the salient portions.

Action Recognition

Learning long-term dependencies for action recognition with a biologically-inspired deep network

1 code implementation ICCV 2017 Yemin Shi, Yonghong Tian, Yao-Wei Wang, Tiejun Huang

Despite a lot of research efforts devoted in recent years, how to efficiently learn long-term dependencies from sequences still remains a pretty challenging task.

Action Recognition

Sequential Deep Trajectory Descriptor for Action Recognition with Three-stream CNN

no code implementations10 Sep 2016 Yemin Shi, Yonghong Tian, Yao-Wei Wang, Tiejun Huang

Nevertheless, most of the existing features or descriptors cannot capture motion information effectively, especially for long-term motion.

Action Recognition

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