Deep Learning for Vision, Imaging and Metrology

This session explores the application of deep learning in vision, imaging, and precision measurement, where it is driving significant innovation. In computer vision, it transforms image and video analysis, 3D reconstruction, and robotic vision. In optical imaging, deep learning enhances computational imaging, boosts resolution and accuracy in medical and biological imaging, and integrates multi-modal systems for better diagnostics. The session also covers deep learning’s role in optical measurement, advancing high-precision metrology, 3D surface measurement, and wavefront sensing. Additionally, the latest innovations in deep learning algorithms will be discussed, highlighting their impact on emerging fields like augmented reality, automated inspection, and precision manufacturing.

Submissions are solicited on, but not limited to, the following topics:

• Deep Learning for Computer Vision (Image/Video Analysis, 3D Reconstruction, Vision for Robotics )
• Deep Learning for Optical Imaging (Computational Imaging, Medical/Biological Imaging, Multi-modal Imaging )
• Deep Learning for Optical Measurement (High-precision Metrology, 3D Surface Measurement, Wavefront Sensing & Aberration Correction)
• Innovative Deep Learning Algorithms and other Applications

Organizing Chairs

Dr. Xiang Peng, Shenzhen University & Shenzhen Anhua Co., Ltd., China
Dr. Guohai Situ, Shanghai Institute of Laser Technology, China

Committee Members

Dr. Yu Fu, Shenzhen University, China
Dr. Peng Gao, Xidian University, China
Dr. Jun Ma, Nanjing University of Science and Technology, China
Dr. Caojin Yuan, Nanjing Normal University, China
Dr. Lei Lu, Henan University of Technology, China
Dr. Wenqi He, Shenzhen University, China