2 GRA Vacancy for Automated Detection of Visual and Speech Contents for Film Censorship using Deep Learning Project

University / Institute: Multimedia University
Research Center/Lab (optional):
Project Title:

Automated Detection of Visual and Speech Contents for Film Censorship using Deep Learning

Start Date 2 Jan 2019
End Date: 30 Nov 2020
Funding Agency: Telekom Malaysia R&D Grant
Contact Email(s): hezerul@mmu.edu.my
Contact Phone(s):
03-83125499
Nationality Requirements on Candidate(s): Local or Foreigner
Research Scholar 1
Monthly Salary: RM2500 (To pursue Masters full time) (depending upon candidate’s experience).
Main Task: Data collection, algorithm development and simulation for audio censorship.
Main Requirement: Bachelor’s degree with honours in Electronics/Electrical/Computer Engineering/Computer Science discipline, preferably 2nd class or above.Research Scholar 2
Monthly Salary: RM3000 (To pursue PhD full time) (depending upon candidate’s experience).
Main Task: Data collection, algorithm development and simulation for video censorship.
Main Requirement: Master’s degree with honours in Electronics/Electrical/Computer Engineering/Computer Science discipline, preferably 2nd class or above.

Location: Faculty of Engineering, MMU Cyberjaya
Benefits of the project (not limited to):
-Attending local conference(s) based on oneself effort in publication.

Responsibilities:
•    To evaluate public nudity scene video dataset and prepare offensive /foul language data set.
•    To implement and evaluate existing techniques on public data set and newly created offensive audio dataset. To do testing on video/audio data provided by UNIFI TV.
•    To perform coding using Python.
•    To develop, train and evaluate CNN for nudity scene detection in video stream.
•    To develop, train and evaluate RNN to detect foul languages in video.
•    To do any relevant administrative work/purchasing matters as requested.
•    Research and publication work.

Other Requirements:
•    Good knowledge of image and video processing.
•    Good English proficiency.
•    Self-motivated, requires minimal supervision, resourceful, keen to learn, possess good communication skills and able to work under pressure.
•    The candidate ideally should be proficient in Python scientific programming. This project uses the deep learning technology for video and audio classification. Therefore, candidate that have completed the course Practical Deep Learning For Coders, Part 1 at
http://course.fast.ai/ will have an added advantage.
•    Deep learning knowledge will mainly be evaluated based on previous completed projects

 

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https://ieeemy.org/mysection/category/jobposition-vacancy/

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