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S&T Best Computing Projects
Visually impaired assistant with neural network and image recognition
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Visually impaired assistant with neural network and image recognition - PDF
Visually impaired assistant with neural network and image recognition - video
/sw/islandora/object/stcompfyp%3A8/datastream/OBJ/view
Collection
S&T Best Computing Projects
Record Details
Record ID
stcompfyp:7
Title
Visually impaired assistant with neural network and image recognition
Type of Work
Final Year Project/Work
Collection
S&T Best Computing Projects
Contributor
Liu, On Chun Arthur 廖安駿 (group member)
Li, Shun Ki 李順麒 (group member)
Yan, Liqi (group member)
Ng, Sin Chun Vanessa 吳倩珍 (supervisor)
School / Unit
School of Science and Technology (S&T)
Program
Bachelor of Computing with Honours in Internet Technology
Date
2020
Abstract
The aim of this project is to implement a visually impaired assistant with neural network and image recognition to help visually impaired go outside efficiently and safely. The visually impaired assistant will be similar to a person to accompany the user, using the image recognition technology to describe the nearby environment to the visually impaired in real- time, letting them know what is going on in front of them. The obstacle detector will let them know the obstacles ahead so that they can be prepared early.
Type of Resource
Mixed
Language
English
Physical Description
This work includes 1 PDF and 1 video clip.
Awards
Champion, Final Year Project (FYP) Competition (17th), 2020 (IEEE(HK) Computational Intelligence Chapter, Institute of Electrical and Electronics Engineers Hong Kong Section)
Notes
Team name : Cyberdyne
Keywords
people with visual disabilities--services for; human-computer interaction; image processing; neural networks (computer science)
Access Eligibility
Public Access
Permanent Link
https://repository.lib.hkmu.edu.hk/sw/islandora/object/stcompfyp:7
Object Details
Record ID
stcompfyp:8
Title
Visually impaired assistant with neural network and image recognition - PDF
Collection
S&T Best Computing Projects
Type of Resource
PDF
Physical Description
5 pages.
Access Eligibility
Public Access
Permanent Link
https://repository.lib.hkmu.edu.hk/sw/islandora/object/stcompfyp:8
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