Live-Stream


Introduction to Optical Payloads in Space Missions

10 December  10:00 am ET

Abstract: Instruments or sensors and the associated software aboard a satellite or spacecraft are referred to as payloads. Payloads sense or interact with the subject to fulfill the objectives of space missions. Payloads are typically unique to each space mission and are the fundamental reason why the satellites are flown. Optical payloads are widely used in space missions. They measure reflective light in wavelength range from ultraviolet, visible to infrared. Optical payloads are the core of many space missions including Earth observation, space exploration, astronomy, imagery, surveillance, etc. They largely dominate the mission’s cost, complexity, and effectiveness. In this lecture, Dr. Qian will provide an introduction to optical payloads in space missions. He will briefly describe six kinds of optical payloads, including hyperspectral imagers, multispectral imagers, Fourier transform spectrometers, lidar and active sensors, radiometers and spectrometers, and other type optical sensors. For each kind of payloads, he will present one or two well-known payloads as examples and their associated missions and applications.

Speaker
Dr. Shen-En Qian received his Ph.D. in Telecommunication and Electronic Systems in 1990. He is a top government scientist at the Canadian Space Agency (CSA) for near 30 years and a world recognized expert in spacecraft optical payloads. As a sole author/editor, he has published four books on optical satellites, system design and signal processing (Optical Payloads for Space Missions, Hyperspectral Satellite and System Design, Optical Satellite Signal Processing and Enhancement, Optical Satellite Data Compression and Implementation). He is a Technical Lead of space missions and Scientific Authority of government R&D contracts awarded to industry and academia in the development of space technologies for satellite missions and deep space exploration. Dr. Qian holds 35 patents granted worldwide developed in Canadian government laboratories. He has published over 120 scientific papers. He received the IEEE Canada Outstanding Engineer Award and Silver Medal in 2019. The Governor General of Canada presented him with the prestigious national award “Public Service Awards of Excellence” in the category Scientific Contribution. He was the first recipient of the Canadian Government Invention Award at the CSA. He received the Marie Curie Award issued by the European Union. He is an Associate Editor of the Journal for the Applied Remote Sensing, and IEEE J-MASS. He is an adjunct professor at York University. Dr. Qian is a fellow of the Canadian Academy of Engineering (CAE), a fellow of the International Society of Optics and Photonics (SPIE), and a Senior Member of IEEE.


Abstract:

GPU/accelerator architectures have greatly improved the training and inferencing speed for neural-network-based machine learning models. As major industry players race to develop ambitious applications such as self-driving vehicles, unstructured data analytics, human-level interactive systems, and human intelligence augmentation, major challenges remain in computational methods as well as hardware/software infrastructures required for these applications to be effective, robust, responsive, accountable and cost-effective. These applications impose much higher levels of data storage capacity, access latency, energy efficiency, and throughput. In this talk, I will present a vision for building a new generation of computing components and systems for these applications.

Speaker’s Bio:

Wen-mei W. Hwu is a Professor and holds the Sanders-AMD Endowed Chair in the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign. He is the director of the IMPACT research group (www.crhc.uiuc.edu/Impact). He co-directs the IBM-Illinois Center for Cognitive Computing Systems Research (C3SR) and serves as one of the principal investigators of the NSF Blue Waters Petascale supercomputer. For his contributions, he received the ACM SigArch Maurice Wilkes Award, the ACM Grace Murray Hopper Award, the IEEE Computer Society Charles Babbage Award, the ISCA Influential Paper Award, the IEEE Computer Society B. R. Rau Award and the Distinguished Alumni Award in Computer Science of the University of California, Berkeley. He is a fellow of IEEE and ACM. Dr. Hwu received his Ph.D. degree in Computer Science from the University of California, Berkeley.

Description

The Low Power Image Recognition Challenge (LPIRC) 2019 is a one-day workshop that will extend the successes of LPIRC from the past four years, identifying the best computer vision solutions that can simultaneously achieve high accuracy and energy efficiency. Since the first competition, held in 2015, the winners’ solutions have improved 24x in the ratio of accuracy divided by energy.

The live-stream of LPIRC will feature presentations from researchers and last year's winner (all times PDT):

09:30-09:40 - Welcome by Organizers and Summary of Online Challenge

09:40-10:30 - 2018 competition winners will give a talk on their winning solutions — Amazon's Tao Sheng, and Expasoft's Alexander Goncharenko and Sergey Alyamkin

10:30-11:10 - Invited Talk: Rethinking the Computations in Computer Vision (and the Hardware that Computes Them) - UC Berkeley's Kurt Keutzer

11:10-13:40 - Live-stream will shut down temporarily

13:40-14:00 - Invited Talk: Visual Wake Words Challenge - Google's Aakanksha Chowdhery and Pete Warden

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  • Additional Speaker

    Title, Company

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    Title, Company

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Gingerbread oat cake powder carrot cake. Lemon drops pie icing. Cotton candy jelly halvah sesame snaps jelly powder danish. Pie sweet roll cake lollipop cake. Icing pie dragée gummies jelly soufflé carrot cake chupa chups chocolate. Cake pie jujubes chocolate cake marshmallow topping tart tiramisu. Tootsie roll cupcake halvah sweet muffin. Bear claw jelly lemon drops dessert dessert.

  • Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

    > Read More

  • Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

    > Read More

  • Brownie sesame snaps candy canes. Wafer muffin powder chocolate bear claw bonbon pastry. Topping caramels carrot cake marshmallow soufflé icing.

    > Read More

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