Prof. Hajime Nagahara
Osaka University, JapanDeep Sensing: Jointly optimizing imaging and processing
Abstract:
Deep neural network (DNN) is a powerful tool for solving image processing and computer vision tasks such as image and video reconstructions, object recognition, and scene understanding, etc. However, DNN have been used for only digital domain in the imaging pipeline, such as the feature extractor and classifier models after an image is captured and digitized. In this research, we propose a new framework called "deep sensing". The proposed framework also models the analog layer to the neural network model and jointly optimizes the parameters in optics and sensor designs of a camera, as well as reconstruction and classification models by the same training strategy.
Biography:
Hajime Nagahara is a professor at D3 Center, Osaka University, since 2024. He received Ph.D. degree in system engineering from Osaka University in 2001. He was a research associate of the Japan Society for the Promotion of Science from 2001 to 2003. He was an assistant professor at the Graduate School of Engineering Science, Osaka University, Japan from 2003 to 2010. He was an associate professor in Faculty of information science and electrical engineering at Kyushu University from 2010 to 2017. He was a professor at Institute for Datability Science, Osaka University, from 2017 to 2024.
He was a visiting associate professor at CREA University of Picardie Jules Verns, France, in 2005. He was a visiting researcher at Columbia University in 2007-2008 and 2016-2017.
Computational photography and computer vision are his research areas. He received IPSJ Nagao Special Researcher Award in 2012, ICCP2016 Best Paper Runners-up, and SSII Takagi Award in 2016. He is a program chair for ICCP2019, General Chair for upcoming ACCV2026 Osaka, Associate Editor for IEEE Transaction on Computational Imaging in 2019-2022, and Director of Information Processing Society of Japan in 2022-2024.
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