Devices that See and Learn – Talk by Dr Anil Bharath

When:
December 1, 2015 @ 4:30 pm – 5:30 pm
2015-12-01T16:30:00+00:00
2015-12-01T17:30:00+00:00
Where:
Lecture Theatre B, Department of Experimental Psychology
Department of Experimental Psychology
S Parks Rd, Oxford, Oxford OX1 3UD
UK
Cost:
£2 / Free for members
Contact:
Marco Narajos
07463658843

Wine reception, snacks, and £5 year membership to PsyNAppS available. Alternatively, pay £2 for a single event!

Venue: Lecture Theatre B, Department of Experimental Psychology

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Dr. Anil Anthony Bharath is Reader in Image Analysis, and on the Research Board of Imperial’s Data Sciences Institute. He holds a degree in Electrical & Electronic Engineering from UCL, and obtained a PhD from Imperial College, also from the Department of Electrical & Electronic Engineering.

He was appointed as Lecturer in the Department of Biological & Medical Systems at Imperial College in 1991. Between 1993 and 2003, Dr.Bharath held the posts of Hayward Lecturer, then Hayward Senior Lecturer in Medical Imaging. He was appointed to a Readership position in 2005.

Dr. Bharath has published in the field of imaging, image analysis, and signal processing, and has 20 years’ experience in signal processing. In 1998, he demonstrated the first application of steerable filters to shape detection, an area of image analysis. Later contributions included the use of Bayesian marginalisation in very early-stage computer vision, focus-of-attention methods, and the use of customised wavelet transforms to analyse images in a scalable manner. The analysis of visual data, including new algorithms and system architectures, continues to be his main research interest.

In 2002, Dr. Bharath initiated the Basic Technology Project “Reverse Engineering Human Visual Processes”, which created a blueprint for a subset of processes in the human visual system, particularly of visual area V1.

In 2008, Dr. Bharath spun out the company Cortexica Vision Systems, which applies spatial neuronal models, expressed through the use of two-dimensional, complex wavelet decompositions, to visual search, both at video rates and on mobile devices.

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