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Proposer
Md Azher Uddin
Title
Handwriting-Based Gender Classification Using deep and handcrafted feature fusion
Goal
Gender Classification based on Handwriting text using ML and computer vision
Description
Resources
Background
Url
Difficulty Level
Moderate
Ethical Approval
None
Number Of Students
0
Supervisor
Md Azher Uddin
Keywords
Degrees
Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Bachelor of Science in Information Systems
Bachelor of Science in Software Development for Business (GA)
Master of Engineering in Software Engineering
Master of Design in Games Design and Development
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Business Information Management
Master of Science in Computer Science for Cyber Security
Master of Science in Computer Systems Management
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Human Robot Interaction
Master of Science in Information Technology (Business)
Master of Science in Information Technology (Software Systems)
Master of Science in Network Security
Master of Science in Robotics
Master of Science in Software Engineering
Bachelor of Science in Computing Science
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