DESCRIPTION
This short course on Deep Learning and Computer Vision for Industrial Infrastructure Inspection offers a comprehensive overview and in-depth presentation of various computer vision and deep learning challenges encountered during the inspection of industrial infrastructures. More specifically, it offers a comprehensive overview of deep learning techniques for detection, segmentation and 3D localization, using data received from a variety of sources, such as visual cameras, LIDAR, thermal cameras, X-ray sensors, and Pulsed Eddy Current (PEC) measurements. The use of many state-of-the-art DNN models, like SAM for semantic image segmentation, YOLO and RT-DETR for object detection and Patchcore for anomaly detection, is also examined.
The course is divided into three lectures:
(a) ‘Electrical Infrastructure Inspection’,
(b) ‘Elongated object detection, segmentation and tracking’ and
(c) ‘Industrial Pipeline Infrastructure Inspection’.
This Short Course presents recent deep learning and computer vision advances as applied in industrial infrastructure inspection (Horizon Europe SIMAR project).
CVML WEB LECTURE MODULE SCHEDULE
This module has been designed to be mastered within 1 month (or less), if you have proper background (at least early undergraduate student in an EE, ECE, CS, CSE or any Engineering or Exact Sciences Department).
We propose that you follow the above mentioned Lecture order. You may want to skip few Lectures that might not be of immediate interest to you for later study.
On average you can study 4 lectures per week. The related effort is as follows:
Lecture pdf study and filling the related understanding questionnaire: 1-2 hours per lecture (on average, depending on your background).
LECTURE LIST
- Electrical Infrastructure Inspection
- Elongated object detection, segmentation and tracking
- Industrial Pipeline Infrastructure Inspection
LECTURER SHORT CV
Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and Ph.D.Degree in Electrical Engineering, both from the Aristotle University of Thessaloniki, Greece. Since 1994, he has been a Professor at the Department of Informatics of the same University. He served as a Visiting Professor at several Universities. His current interests are in the areas of image/video processing, machine learning, computer vision, intelligent digital media, human centered interfaces, affective computing, 3D imaging and biomedical imaging. He is also chair of the Autonomous Systems initiative.