About Me
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Received my B.Sc. and Ph.D. degrees in Electrical Engineering from Tel Aviv University, Israel where I am Full Professor of electro-optics.
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Has authored more than 220 technical articles, 3 book chapters, and is the holder of more than 140 patents all of them have been commercialized. I am the 1998 winner of ICO International Prize in Optics Ernst Abbe Medal by Carl Zeiss. I am a Fellow of The Optical Society of America.
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Founder of successful opto-electronics startup companies (e.g. Civcom and Eyesquad) and served as their CEO. Civcom Inc. was acquired by Padtec S/A of Brazil, Eyesquad was acquired by Tessera Inc (NASDAQ symbol: TSRA) and that was acquired by Samsung.
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Since January 2008 till December 2010, I was the Chief Scientist of the Israeli Ministry of Science. Also acted 6 years as the Co-Chair of GIF (German Israeli Foundation). Served 10 years as Vice Dean for Research of the Faculty of Engineering. At present I serve as the head of TAU Innovation Labs and a board member of the Israel Innovation Authority (IIA). I founded various novel academic programs, TAU Ventures VC and founder and Head of Zimin Institute for Engineering Solutions Advancing Better Lives.
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My research activities provided several worldwide breakthroughs such as hollow fibers for IR transmission; extended depth of field imaging; multi aperture imaging and folded camera; the fractional Fourier transform; depth sensing and image processing.
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Areas Of Research
• Computational photography and its use for miniature imaging systems
• Advanced 3-D sensing and mapping devices based on a single aperture
• AI based image processing algorithms and pipelines
• Advanced authentication systems and methods
• Continues optical sensing of bio-mechanical parameters
• Image processing algorithms for deep-fake
My Latest Publications
Deep Sparse Light Field Refocusing
Shachar Ben Dayan, David Mendlovic, Raja Giryes
Computer Science > Computer Vision and Pattern Recognition
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Light field photography enables to record 4D images, containing angular information alongside spatial information of the scene. One of the important applications of light field imaging is post-capture refocusing. Current methods require for this purpose a dense field of angle views; those can be acquired with a micro-lens system or with a compressive system.
Both techniques have major drawbacks to consider, including bulky structures and angular-spatial resolution trade-off. We present a novel implementation of digital refocusing based on sparse angular information using neural networks. This allows recording high spatial resolution in favor of the angular resolution, thus, enabling to design compact and simple devices with improved hardware as well as better performance of compressive systems.
We use a novel convolutional neural network whose relatively small structure enables fast reconstruction with low memory consumption. Moreover, it allows handling without re-training various refocusing ranges and noise levels. Results show major improvement compared to existing methods.
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