Research Assistant: Tropical Wood Identification using Deep Learning

Research Assistant (RA):
Tropical Wood Identification using Deep Learning

Number of Vacancies: 1 or 2

Available at 

Lee Kong Chian Faculty of Engineering and Science,
Universiti Tunku Abdul Rahman (UTAR) KL Campus,
Jalan Genting Klang, 53300 Kuala Lumpur

Project Title

Tropical Wood Identification using Deep Learning

Project Leader

Dr. Tay Yong Haur (tayyh@utar.edu.my),
Department of Internet Engineering and Computer Science,
Lee Kong Chian Faculty of Engineering and Science (LKCFES),
UTAR KL Campus.

Objective

Identification of wood species based on its anatomy is critical to possibly trace the origin of the wood and hence reduce wood smuggling and illegal logging. Automated process in identification of wood species will create a vast applications from this capability.

In this research, we will look into applying deep learning and convolution neural networks, as the fundamental components in this wood identification system. We aim to devise a novel method to create a platform for applying machine learning in solving the very challenging and exciting research frontiers.

Scope of Work

• To review the recent work in vision-based wood species identification
• To devise and enhance deep learning model for textural feature extraction recognition
• To assess the performance of the model
• To create a proof-of-concept prototype of a wood species identification system

Job Description

• Remuneration of RM1500-2500 per month for 12 to 18 months, depending on experience.
• The RA must help the project leader in all works associated with the research.
• The RA must work closely with the sponsored industry partner to complete the research project.
• The RA may register for Master's degree by research or PhD program with UTAR.

Requirements

• Passionate in computer programming
• Have good mathematical foundations
• Strong interest and/or has working experience in machine learning/artificial intelligence/computer vision/image processing projects.
• Good English written and verbal communication
• Good analytical skills
• Self-motivated, requires minimal supervision, resourceful and willing to learn.
• Available to start working preferably on 1 Jan 2015.

Interested Candidate

If you are interested in the RA position advertised above, please email your CV directly to Dr. Tay Yong Haur (tayyh@utar.edu.my) as soon as possible. Feel free to write to Dr Tay for any further inquiry of the project.

Only short-listed candidates will be called for interview.