Researcher Database

（Last updated : 2025-04-09 18:14:44）　

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OKURA SHUNSUKE

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

Title / Position 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.	2024/04/01 ～	Professor │ College of Science and Engineering │ Ritsumeikan University
2.	2019/04/01 ～ 2024/03/31	Associate Professor │ │ Ritsumeikan University
3.	2014/10/01 ～ 2019/03/31	Senior Image Sensor Scientist │ │ BRILLNIS Japan Inc.,

Committee and society
1.	2024/10/01 ～	2025 Symposium on VLSI Technology and Circuits Program Committee
2.	2020/04/01 ～ 2024/03/31	IEICE
3.	2020 ～	IST

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.	2025/02/27	Clean-Label Backdoor Attack against Object Detector Triggered by Fault Injection into MIPI │ Proceedings of the 2025 International Workshop on Nonlinear Circuits, Communication and Signal Processing │ ,pp.28PM2-2-6
2.	2024/11/05	Implementation of an Image Tampering Detection System with a CMOS Image Sensor PUF and OP-TEE │ Sensors, MDPI AG │ 24 (22:7121)
3.	2024/11/01	Image Classification Using Neural Network for Feature-Extractable CMOS Image Sensor │ Journal of Signal Processing │ 28 (6),pp.301-307
4.	2024/09/20	Defense Method Against Adversarial Example Attacks using Thermal Noise of a CMOS Image Sensor │ 2024 IEEE SENSORS │ ,pp.1-4
5.	2024/09/20	Lightweight Object Detection Model for a CMOS Image Sensor with Binary Feature Extraction │ 2024 IEEE SENSORS │ ,pp.1-4
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Works
1.	2023/03/31	エッジAIに向けたCMOSイメージセンサの検討

Winning science prize
1.	2024/01/08	International Workshop on Advanced Image Technology Best Paper Award
2.	2023/03/01	RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing Student Paper Award
3.	2019/06	IISS International Image Sensor Workshop IISS BEST POSTER AWARD, THE THIRD PLACE
4.	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.		Solid-state imaging device, method for manufacturing solid-state imaging device, and electronic apparatus （10,341,597）
2.		Solid-state imaging device, method for fabricating solid-state imaging device, and electronic apparatus （12107095）
3.	2019/07/17	Solid-state imaging device, method for fabricating solid-state imaging device, and electronic apparatus （16/514,298）
4.		Solid-state imaging device, method for driving solid-state imaging device, and electronic apparatus with physically unclonable function （10,382,708）
5.		Solid-state imaging device, method for driving solid-state imaging device, and electronic apparatus having an amplifier with an inverting input terminal having at least a first inverting input channel and a second inverting input channel （11,070,761）
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