Xiaowei Zhou

Xiaowei Zhou

Lecturer

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Pages

Posts

Run matlab on Ubuntu

less than 1 minute read

Published:

Windows远程连接Ubuntu，上传文件并运行matlab

Install Caffe on ubuntu

less than 1 minute read

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【转载】Caffe + Ubuntu 15.04 + CUDA 7.5 新手安装配置指南

Connect to ubuntu

less than 1 minute read

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Windows（xrdp+vnc）远程连接Ubuntu系统

Files full on disk

less than 1 minute read

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ubuntu系统磁盘已满，导致系统无法启动

portfolio

publications

Human-Understandable Decision Making for Visual Recognition.

Published in Pacific-Asia Conference on Knowledge Discovery and Data Mining PAKDD, 2021

The widespread use of deep neural networks has achieved substantial success in many tasks. However, there still exists a huge gap between the operating mechanism of deep learning models and human-understandable decision making, so that humans cannot fully trust the predictions made by these models. To date, little work has been done on how to align the behaviors of deep learning models with human perception in order to train a human-understandable model. To fill this gap, we propose a new framework to train a deep neural network by incorporating the prior of human perception into the model learning process. Our proposed model mimics the process of perceiving conceptual parts from images and assessing their relative contributions towards the final recognition. The effectiveness of our proposed model is evaluated on two classical visual recognition tasks. The experimental results and analysis confirm our model is able to provide interpretable explanations for its predictions, but also maintain competitive recognition accuracy.

Recommended citation: @inproceedings{zhou2021human, title={Human-Understandable Decision Making for Visual Recognition}, author={Zhou, Xiaowei and Yin, Jie and Tsang, Ivor and Wang, Chen}, booktitle={Pacific-Asia Conference on Knowledge Discovery and Data Mining}, pages={168--180}, year={2021}, organization={Springer} } https://link.springer.com/chapter/10.1007/978-3-030-75768-7_14

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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