微芯学堂第三十三讲:Bioinspired in-sensor computing for artificial vision
黄之诚 2024-04-15 5441

题目:Bioinspired in-sensor computing for artificial vision 

时间:2024年4月18日(周四)10:30

地点:国际校区C1-b114

主讲人:Sorin Cristoloveanu 

       

Abstract

The visual scene in the physical world integrates multidimensional information (spatial, temporal, polarization, spectrum, etc) and typically displays unstructured characteristics. Conventional image sensors cannot process this multidimensional vision data, creating a need for vision sensors that can efficiently extract features from substantial multidimensional vision data. Vision sensors are able to transform the unstructured visual scene into featured information without relying on sophisticated algorithms and complex hardware.

In this talk, I will describe our team’s efforts towards bioinspired in-sensor computing for artificial vision. I will talk about the framework of the in-sensor computing and demonstrate a few vision sensors for different scenarios, including visual adaptation, motion perception, as well as event-driven vision sensors for spiking neural network.

Introduction

Prof. Yang Chai is the Associate Dean of the Faculty of Science, Director of Joint Research Center of Microelectronics of the Hong Kong Polytechnic University, Vice President of the Physical Society of Hong Kong, a member of The Hong Kong Young Academy of Sciences, an IEEE Distinguished Lecturer since 2016, the Vice Chair of IEEE EDS region 10, the Chair of IEEE EDS Nanotechnology Committee, and was the Chair of IEEE ED/SSC Hong Kong Chapter (2017-2019). His current research interest mainly focuses on emerging electronic devices.

References

[1] Nature Electronics, 2022, 5, 84-91

[2] Nature, 2022, 602, 364

[3] Nature Electronics, 2020, 3, 664-671

[4] Nature, 2020, 579, 32-33

[5] Nature Nanotechnology, 2019, 14, 776-782

[6] Nature Electronics, 2022, 5, 483-484

[7] Nature Nanotechnology, 2023, 18, 882-888

[8] Nature Electronics, 2023, 6, 870-878

[9] Nature Nanotechnology, 2024, accepted

[10] IEEE IEDM, 2022, 739-742