Advanced Methods and Deep Learning in Computer Vision

About the author

Roy Davies was Emeritus Professor of Machine Vision at Royal Holloway, University of London. He worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests included automated visual inspection, surveillance, vehicle guidance, crime detection and neural networks. He has published more than 200 papers, and three books. Machine Vision: Theory, Algorithms, Practicalities (1990) has been widely used internationally for more than 25 years, and is now out in this much enhanced fifth edition. Roy held a DSc at the University of London and was awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition.Matthew Turk is a professor and department chair of the Department of Computer Science at the University of California, Santa Barbara, California. He was named a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2013[1] for his contributions to computer vision and perceptual interfaces. Starting on July 1st, he will be the president of the Toyota Technological Institute at Chicago[2]. In 2014, Turk was named a Fellow of the International Association for Pattern Recognition (IAPR)[3] for his contributions to computer vision and vision based interaction.

Product details

• Authors: E. R. (EDT)/ Turk Davies
• Assisted by: E. R. (Emeritus Professor of Machine Vision Davies (Editor), Davies E. R. (Editor), Matthew (Professor and Department Chair Turk (Editor), Turk Matthew (Editor)
• Publisher: Academic Press London
• Languages: English
• Product format: Paperback / Softback
• Released: 26.11.2021
• EAN: 9780128221099
• ISBN: 978-0-12-822109-9
• No. of pages: 550
• Series: Computer Vision and Pattern Recognition
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; Robotics, TECHNOLOGY & ENGINEERING / Robotics, TECHNOLOGY & ENGINEERING / Automation, Computer Vision, pattern recognition, Automatic control engineering, Computer Vision; deep learning