Researcher Database

（Last updated : 2022-05-19 10:40:03）

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OKURA SHUNSUKE

Department / Course College of Science and Engineering Department of Electronic and Computer Engineering

Title / Position Associate Professor

Other Affiliations
1.	Graduate School of Science and Engineering

Academic background
1.	2010/09 Degree Acquisition	│ Osaka University Doctor of Philosophy
2.	～1998/03	│ Unebi Senior High School │ Graduated
3.	～2003/03	Division of Electronic, Information and Energy Engineering │ School of Engineering │ Osaka University │ Graduated
4.	～2005/03	Doctoral Program (1st Semester) │ Division of Electrical, Electronic and Information Engineering │ Graduate School of Engineering │ Osaka University │ Completed
5.	～2008/03	Doctorial Course │ Division of Electrical, Electronic and Information Engineering │ Graduate School of Engineering │ Osaka University │ Accomplished credits for doctoral program

Business career
1.	2019/04/01	Associate Professor │ │ Ritsumeikan University
2.	2014/10/01 ～ 2019/03/31	Senior Image Sensor Scientist │ │ BRILLNIS Japan Inc.,

Committee and society
1.	2020 ～	IST
2.	2020 ～	IEICE

Research activities
1.		IEEE
2.		The Institute of Image Information and Television Engineers
3.	2020/06/01 ～	Institute of Electronics, Information and Communication Engineers

Subject of research
1.	Research on vision sensors for an IoT society

Research summary
Research of vision sensors in AI and IoT society In the Internet of things (IoT) society, electronics and sensors can communicate and interact with others over the Internet, and they can be remotely monitored and controlled. Though we conventionally can recognize only a limited range of information with our five senses, we will be able to acquire all information from everywhere in the world with the sensor network that operates as our augmented senses. On the other hand, since the information processing capability of our brain is limited, it is supposed that artificial intelligence (AI) will recognize the information detected by sensors. The recognition results will be shared among devices, and will be used as big data. Vision is our most important sense. Around 80% of the information from the outside that reaches our brains comes via our eyes. Thus, image sensors in the sensor network will be remarkably important in the IoT age. The goal of this research is to develop vision sensors such as image sensors and distance sensors used in the AI and IoT society, and to study their system applications. In particular, this research is composed of the following four sub-researches. 1.Since trillions of ubiquitous sensors will be utilized in the IoT society, they are required to operate with extremely low power consumption from the viewpoint of maintenance and the sustainable society. We are developing an image sensor that detects features at the pixel level for ultra-low power consumption. 2.Image information from everywhere in the world includes outdoor image information. Conventionally, under outdoor sunlight, images are captured at a given exposure focusing on the object the photographer wants to see. However, in order for AI to recognize the scene, high dynamic range (HDR) image is required to avoid halation under sunlight and blocked up shadows. Besides, to recognize moving objects, we are developing an image sensor for single exposure HDR (SEHDR). 3.The conventional image processing subjects to realize a “good” images for human. However, much of image information will be used for AI to recognize the scenes. We are studying signal processing methods for the above extracted feature and HDR images with deep learning. 4In order for the trillions of sensors to communicate with each other, secure communication with extremely low management cost, which prevents attackers from exploiting IoT sensor networks, is required. We are developing secure image sensors that use Physically Unclonable Function (PUF) that utilizes variations caused in the fabrication.

Present specialized field
Electron device/Electronic equipment (Keyword：image sensor, CMOS, analog circuit, A/D converter, pixel device, high dynamic range, wide dynamic range, hardware security, PUF, IoT)

Papers
1.	2022/03/01	Experimental Study of Fault Injection Attack on Image Sensor Interface for Triggering Backdoored DNN Models │ IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences │ E105-A (3) (Co-authored)
2.	2022/02/28	Image Recognition of HDR Images Taken with Dual-Gain CIS │ Proceedings of the 2022 International Workshop on Nonlinear Circuits, Communication and Signal Processing │ ,pp.2PM2-1-1 (Co-authored)
3.	2021/11/15	Backdoor Attack on Deep Neural Networks Triggered by Fault Injection Attack on Image Sensor Interface │ Proceedings of the 5th Workshop on Attacks and Solutions in Hardware Security │ ,pp.63-72 (Co-authored)
4.	2021/09/10	Area-Efficient Post-Processing Circuits for Physically Unclonable Function with 2-Mpixel CMOS Image Sensor │ Sensors, MDPI AG │ 21 (18:6079) (Co-authored)
5.	2021/03/08	Modeling attacks against device authentication using CMOS image sensor PUF │ IEICE Electronics Express │ 18 (7),pp.20210058 (Co-authored)
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Academic conference presentation
1.	2020/02/28	Dependency Evaluation between Performance Metrics and Response-Bit Length of a CIS-PUF (International Workshop on Nonlinear Circuits, Communications and Signal Processing)
2.	2019/06/23	A 2-Mpixel CMOS Image Sensor with Device Authentication and Encryption Key Generation based on Physically Unclonable Function (International Image Sensor Workshop)
3.	2019/06/23	A High Optical Performance 2.8µm BSI LOFIC Pixel with 120ke- FWC and 160µV/eConversion Gain (International Image Sensor Workshop)

Winning science prize
1.	2019/06	IISS International Image Sensor Workshop IISS BEST POSTER AWARD, THE THIRD PLACE
2.	2018/11	2018 International Symposium on Intelligent Signal Processing and Communication Systems Best Paper Award

Grants-in-Aid for Scientific Research -KAKENHI-
1.	2019/08 ～ 2021/03	power scalable column sar adc with interference noise reduction circuit │ Grant-in-Aid for Research Activity start-up

Acquisition patent
1.		Semiconductor device （9,716,851）
2.		Solid-state image pickup device （8,665,354）
3.		Solid-state image sensing device （9,253,423）
4.		Solid-state image sensing device and electronic device （10,038,868）
5.		Solid-state image sensing device and electronic device （9,635,290）
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