TY - BOOK ID - 33241328 TI - Imaging, Vision and Learning Based on Optimization and PDEs : IVLOPDE, Bergen, Norway, August 29 – September 2, 2016 AU - Tai, Xue-Cheng. AU - Bae, Egil. AU - Lysaker, Marius. PY - 2018 SN - 3319912747 3319912739 PB - Cham : Springer International Publishing : Imprint: Springer, DB - UniCat KW - Image processing KW - Digital techniques. KW - Mathematics. KW - Digital image processing KW - Digital electronics KW - Computer vision. KW - Optical pattern recognition. KW - Computer science KW - Mathematical optimization. KW - Differential equations, partial. KW - Computer graphics. KW - Image Processing and Computer Vision. KW - Pattern Recognition. KW - Computational Mathematics and Numerical Analysis. KW - Optimization. KW - Partial Differential Equations. KW - Computer Graphics. KW - Automatic drafting KW - Graphic data processing KW - Graphics, Computer KW - Computer art KW - Graphic arts KW - Electronic data processing KW - Engineering graphics KW - Partial differential equations KW - Optimization (Mathematics) KW - Optimization techniques KW - Optimization theory KW - Systems optimization KW - Mathematical analysis KW - Maxima and minima KW - Operations research KW - Simulation methods KW - System analysis KW - Computer mathematics KW - Discrete mathematics KW - Optical data processing KW - Pattern perception KW - Perceptrons KW - Visual discrimination KW - Machine vision KW - Vision, Computer KW - Artificial intelligence KW - Pattern recognition systems KW - Digital techniques KW - Mathematics KW - Optical data processing. KW - Pattern recognition. KW - Computer mathematics. KW - Partial differential equations. KW - Design perception KW - Pattern recognition KW - Form perception KW - Perception KW - Figure-ground perception KW - Optical computing KW - Visual data processing KW - Bionics KW - Integrated optics KW - Photonics KW - Computers KW - Optical equipment UR - https://www.unicat.be/uniCat?func=search&query=sysid:33241328 AB - This volume presents the peer-reviewed proceedings of the international conference Imaging, Vision and Learning Based on Optimization and PDEs (IVLOPDE), held in Bergen, Norway, in August/September 2016. The contributions cover state-of-the-art research on mathematical techniques for image processing, computer vision and machine learning based on optimization and partial differential equations (PDEs). It has become an established paradigm to formulate problems within image processing and computer vision as PDEs, variational problems or finite dimensional optimization problems. This compact yet expressive framework makes it possible to incorporate a range of desired properties of the solutions and to design algorithms based on well-founded mathematical theory. A growing body of research has also approached more general problems within data analysis and machine learning from the same perspective, and demonstrated the advantages over earlier, more established algorithms. This volume will appeal to all mathematicians and computer scientists interested in novel techniques and analytical results for optimization, variational models and PDEs, together with experimental results on applications ranging from early image formation to high-level image and data analysis. ER -