Home
Mathematical Methods Image Processing and Inverse Problems: IPIP 2018, Beijing, China, April 21-24
Barnes and Noble
Mathematical Methods Image Processing and Inverse Problems: IPIP 2018, Beijing, China, April 21-24
Current price: $199.99


Barnes and Noble
Mathematical Methods Image Processing and Inverse Problems: IPIP 2018, Beijing, China, April 21-24
Current price: $199.99
Size: Hardcover
Loading Inventory...
*Product information may vary - to confirm product availability, pricing, shipping and return information please contact Barnes and Noble
This book contains eleven original and survey scientific research articles arose from presentations given by invited speakers at International Workshop on Image Processing and Inverse Problems, held in Beijing Computational Science Research Center, Beijing, China, April 21–24, 2018. The book was dedicated to Professor Raymond Chan on the occasion of his 60th birthday.
The contents of the book cover topics including image reconstruction, image segmentation, image registration, inverse problems and so on. Deep learning, PDE, statistical theory based research methods and techniques were discussed. The state-of-the-art developments on mathematical analysis, advanced modeling, efficient algorithm and applications were presented. The collected papers in this book also give new research trends in deep learning and optimization for imaging science. It should be a good reference for researchers working on related problems, as well as for researchers working on computer vision and visualization, inverse problems, image processing and medical imaging.
The contents of the book cover topics including image reconstruction, image segmentation, image registration, inverse problems and so on. Deep learning, PDE, statistical theory based research methods and techniques were discussed. The state-of-the-art developments on mathematical analysis, advanced modeling, efficient algorithm and applications were presented. The collected papers in this book also give new research trends in deep learning and optimization for imaging science. It should be a good reference for researchers working on related problems, as well as for researchers working on computer vision and visualization, inverse problems, image processing and medical imaging.