Course outline ADSP - Summary Deep learning PDF

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In the name of God

Department of Advanced Medical technologies

Advanced Digital Signal Processing (ADSP) Spring 2019 Course Overview Instructor: Rahele Kafieh Email: [email protected] Telephone: +98 31 37925261 Lectures: 8-14, Monday, the course web page should be frequently visited throughout the semester. Summary: The goal of this course is to introduce new techniques used for classification and analysis of digital images and to provide applicable algorithms for automatic processing of these images. Website: https://app.schoology.com/ Access code: RRPZZ-T8HSZ This password protected web site will serve as the mechanism for information exchange in this course. That is, all course notes, projects, problem sets, solutions, and any other handouts will be made available through this web site. Class announcements will also be made through the web site. Thus, the course web page should be frequently visited throughout the semester. Syllabus: 

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Deep Learning Python Programming Introduction to Deep Learning Build deep learning with Keras Stepping up to image Convolution Neural Networks Image classification Image segmentation Atomic representation Frames, tight frames, ...

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Representation with fixed atoms 2D Xlets Complex wavelet Ridgelets Curvelets Contourlets Bandlets 3D Xlets Surfacelet 3D curvelet 3D complex wavelet Representation with adaptive atoms (Dictionary learning) Dictionary learning methods calculation of the coefficients MP, BP, OMP Batch and online methods Energy based processing PDE based Image Processing Active models Active Shape models Active Appearance Models Active Mesh Models

Assignments: There will be several homework and assignments. These will be available on the course website. Useful Textbooks: (available in the library or can be downloaded from http://gen.lib.rus.ec) 1- Chollet, Francois. Deep learning with python. Manning Publications Co., 2017. 2- Peyré, Gabriel, Advanced Signal, Image and Surface Processing 3- Chan, Tony F., Jianhong Shen, and Luminita Vese. "Variational PDE models in image processing." Notices AMS 50 (2003): 14-26. 4- Mallat, Stephane. A wavelet tour of signal processing: the sparse way. Academic press, 2008. 5- Starck, Jean-Luc, Fionn Murtagh, and J. Fadili. "Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity." (2011)....