Date: 16 Oct 2014 (Thursday)
Time: 10.30am - 11.30am
Venue: Meeting room, Mimos Lab, SB Ground Floor, FES, UTAR Kuala Lumpur Campus.
Title: A study on HMAX
Abstract:
This talk covers some popular ANN architectures, starting from the basic 3-layer backpropagation network to the more recently popular deep architectures, which include the convolutional network and HMAX. The author will share the details of his HMAX study and describe the latest sparse coding addition to the existing model, which gave a drastic improvement on the challenging Caltech-101 benchmark. He will end his talk with a discussion on which future direction to take: deep or broad. This talk is suitable for image processing and ANN researchers, or anyone interested in brain intelligence.
Speaker: Francis Lau Kean Hong, Lecturer, UTAR.
Biography:
Francis Lau graduated from Monash University with double degrees of Computer Science and Electrical & Computer System Engineering (Hons) in 1993 and 1995 respectively. He holds a Master degree in Engineering specializing in range (2.5D) image processing. His career involves image inspection, banking and online systems, and taught at UTAR in the Electrical & Electronics Department since 2007. He is currently doing a PhD research project at UTAR on the topic of artificial neural network (ANN) in visual object recognition.
Biography:
Francis Lau graduated from Monash University with double degrees of Computer Science and Electrical & Computer System Engineering (Hons) in 1993 and 1995 respectively. He holds a Master degree in Engineering specializing in range (2.5D) image processing. His career involves image inspection, banking and online systems, and taught at UTAR in the Electrical & Electronics Department since 2007. He is currently doing a PhD research project at UTAR on the topic of artificial neural network (ANN) in visual object recognition.
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