Video Dataset Based on Automated Cover Tests for Strabismus Evaluation

 

Video Dataset Based on Automated Cover Tests for Strabismus Evaluation

This video dataset based on the automated cover tests for strabismus evaluation (VD-ACTSE dataset) was developed to provide a useful dataset for the evaluation of strabismus. The video is acquired when the subject performs the automated cover tests. 24 samples were collected. The video was configured to have a resolution of 1280*720 pixels at a frame rate of 60 fps at a length of about 50s.

If you are interested in the dataset, please feel free to send an email entitled “VD-ACTSE dataset request” to hongfu@chuhai.edu.hk.

 

 

 

 

Figure 1 Some example frames of the video dataset

Light Field-based Face Spoofing Attack Dataset (LF-SAD)

The LF-SAD dataset was developed to provide a useful dataset for the evaluation of the light field-based face spoofing attack detection. It consists of three spoofing attack types—high definition printed photo, warped printed photo, and a high definition screen displayed photo. All photos in this database were captured by Lytro ILLUM light field camera at Chu Hai College of Higher Education.

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InnoTech Expo 2017: Analyzing the visual-motor coordination of children

PI : Dr. Hong Fu (Department of Computer Science)

Co-I: Professor W L Lo (Department of Computer Science)

 

 

 

 

 

 

 

Development coordination disorder (DCD), also referred to developmental dyspraxia, is a motor disorder in children, affecting around 5%-6% of school-aged children. DCD affects fine and gross motor coordination in children and adults, leading to difficulty in learning, organizing and moderating motor skills, and can have significant long term effects on academic, psychosocial and vocational outcomes.

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Deep Learning Tutorial: A Demonstration of Building A Deep Learning Network Using Tensor Flow

Workshop title  : Deep Learning Tutorial: A Demonstration of Building A Deep Learning Network Using Tensor Flow

Guest Speakers  : Mr. Yalong Jiang from The Hong Kong Polytechnic University

Date  : 2 November 2017

Time  : 2:30pm – 4:00pm

Venue  : M06

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