Miguel Ángel Trujillo Soto (CATEC),
Begoña Arrue (GRVC Robotics lab Team),
Ioannis Pitas (AUTH),
Dimitris Psarras (AUTH),
Christos Papaioannidis (AUTH),
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. The course is divided into four lectures. Two lectures, namely (a) ‘Aerial Robotics for Industrial Inspection and the SIMAR project contribution’ and (b) ‘Drone Imaging for Industrial Infrastructure Inspection,’ provide a comprehensive introduction to inspection techniques for industrial infrastructures and highlight the significant role of drones in this field. The subsequent three lectures, (c) ‘Using Artificial Intelligence and Aerial Robots for defect detection and segmentation in Industrial Inspection of Viaduct’, (d) ‘Visual Detection of Elongated Objects’ and (e) ‘Deep Learning Algorithms for Intelligent Support of Workers,’ will provide an in-depth presentation of deep learning solutions for the safe inspection and maintenance of industrial infrastructure. These advanced techniques find practical application in tasks such as localization, which are of paramount importance in autonomous systems and robotic inspection.
This Short Course presents recent deep learning and computer vision advances as applied in industrial infrastructure inspection (Horizon Europe SIMAR project).
Online Event
All lectures will be delivered online via Zoom (Passcode: 114050).
Please refer to the course page for detailed program information.
This short course is supported by Horizon Europe SIMAR project.
5 hours (5 lectures)
Short Course
Both AIDA and non AIDA students, CS/ECE/EE/AI students/scientists, engineers as well as AI enthusiasts from other scientific disciplines having the necessary mathematical background are welcomed to register free of charge on a First-Come-First-Serve basis. Please find the Registration Form.
If you are an AIDA Student* already, on top of the above registration, enroll on this course using the button "ENROLL ON THIS COURSE" below, so that this course is included on your AIDA Certificate of Course Attendance, upon successful course participation (attendance of at least 80% of the scheduled course lectures).
*AIDA Students should have been registered in the AIDA system already (they are PhD students or PostDocs that belong only to the AIDA Members list.
English
Online e-course