Sparse and Redundant Representations and Their Applications in

Slides:



Advertisements
Similar presentations
Patch-based Image Deconvolution via Joint Modeling of Sparse Priors Chao Jia and Brian L. Evans The University of Texas at Austin 12 Sep
Advertisements

Learning sparse representations to restore, classify, and sense images and videos Guillermo Sapiro University of Minnesota Supported by NSF, NGA, NIH,
蔡秉宸 IEEE Transactions on Image Processing Sch. of Sci., Xi'an Jiaotong Univ., Xi'an, China.
Image Super-Resolution Using Sparse Representation By: Michael Elad Single Image Super-Resolution Using Sparse Representation Michael Elad The Computer.
Digital Image Processing: Revision
New Results in Image Processing based on Sparse and Redundant Representations Michael Elad The Computer Science Department The Technion – Israel Institute.
CSC 212 – Data Structures Prof. Matthew Hertz WTC 207D /
16-311: Introduction to Robotics Lab 2 – Robot Vision January 21, 2015 Sarah Tan Introduction to Robotics – Lab 2, p.1.
Navigating this lesson Getting Started An Introduction to Your NCVPS Course.
CS 115 TA Orientation Fall More students! Enrollment up to sections + night about 22% CS majors (50 on 8/16)
I think you’ll recognize it!. Lifespan Development (5 weeks) Intelligence, Testing & Personality (5 weeks) Abnormal, Treatments & Social Behavior (5 weeks)
Welcome to CS 115! Introduction to Programming. Class URL Please write this down!
Lecture Plan of Neural Networks Purpose From introduction to advanced topic To cover various NN models –Basic models Multilayer Perceptron Hopfield.
Course Introduction CS 2302 SPRING Course Introduction In this part we'll discuss course mechanics. Most of this will apply to all sections of the.
CS 376b Introduction to Computer Vision 04 / 29 / 2008 Instructor: Michael Eckmann.
CSC 212 – Data Structures Prof. Matthew Hertz WTC 207D /
Administrative Issues ICS 151 Winter 2010 Instructor: Eli Bozorgzadeh.
Nixon Essay Part 3: Watergate. Overview Guiding Question: Overall, was the Nixon administration a good or bad thing for the US? Your third body paragraph.
Copyright  1999 by James H. Money. All rights reserved. Except as permitted under United States Copyright Act of 1976, no part of this publication may.
CSC 213 – Large Scale Programming Prof. Matthew Hertz WTC 207D /
April 11, 2001 CMPE CMPE-401 Graduation Project Why is it a compulsory course? Students should learn how to conduct independent research on a new.
Mid-Year Portfolio Review Name Date Advisor. Outline Course 1- Essential Question Course 2- Essential Question Course 3- Essential Question Course 4-
Image Decomposition, Inpainting, and Impulse Noise Removal by Sparse & Redundant Representations Michael Elad The Computer Science Department The Technion.
Winter Parent Meeting Class of th Grade Year Winter Parent Meeting Class of th Grade Year ___________________________________________ Ms.
James Tam Introduction To CPSC 233 James Tam Java Object-Orientation Event driven software.
James Tam Introduction To CPSC 233 James Tam Java Object-Orientation Graphical-user interfaces.
Student Presentation Guidelines Sung-Eui Yoon ( 윤성의 )
Student Presentation Guidelines Sung-Eui Yoon ( 윤성의 )
I think you’ll recognize it!. Lifespan Development (5 weeks) Intelligence, Testing & Personality (4 weeks) Abnormal, Treatments & Social Behavior (5 weeks)
My Research in a Nut-Shell Michael Elad The Computer Science Department The Technion – Israel Institute of technology Haifa 32000, Israel Meeting with.
CSc 120 Introduction to Computer Programing II
UW-Superior V10.7 for Instructors
Advanced Image Processing
History of World War II World War II is the most tragic page in the human history. 50 million people, much more than in any other war, were killed during.
Systems Biology for Translational Medicine
Sparse and Redundant Representations and Their Applications in
Final Exam Study Guide This test will cover Chapters 1-13 in the course book. Review each lecture slide and class notes to narrow your focus of study for.
E-BUSINESS SYSTEMS DESIGN IS 232 T
Understanding Standards An overview of course assessment
Sparse and Redundant Representations and Their Applications in
Sparse and Redundant Representations and Their Applications in
Sparse and Redundant Representations and Their Applications in
L16: Feedback from Design Review
Yaniv Romano The Electrical Engineering Department
Sparse and Redundant Representations and Their Applications in
Sparse and Redundant Representations and Their Applications in
Summary Class 1.
Sparse and Redundant Representations and Their Applications in
Sparse and Redundant Representations and Their Applications in
UMKC Canvas Conference July 20, 2018
WELCOME TO NCA! TEACHERS ORIENTATION.
CSC227: Operating Systems
Sparse and Redundant Representations and Their Applications in
Signals and systems ELEC 305
CS510 Concurrent Systems Jonathan Walpole.
First Semester 1439/1440 Welcome 
Sparse and Redundant Representations and Their Applications in
Sparse and Redundant Representations and Their Applications in
Course Outline Highlights
Improving K-SVD Denoising by Post-Processing its Method-Noise
Aim: How can we perform to our greatest potential in Global History?
A study guide for students.
Sparse and Redundant Representations and Their Applications in
Sparse and Redundant Representations and Their Applications in
New Student Orientation
New Student Orientation
Summary Class 1.
Welcome.
Announcements made Tuesday, April 30
Presentation transcript:

Sparse and Redundant Representations and Their Applications in Signal and Image Processing (236862) Section 5 & 6: Image Separation, Inpainting & Super-Resolution Winter Semester, 2018/2019 Michael (Miki) Elad

Meeting Plan Quick review of the material covered Answering questions from the students and getting their feedback Discussing a new material – CSC and the relation to … Deep-Learning Administrative issues

Overview of the Material Image Separation & Inpainting Morphological Component Analysis: The Core Idea Cartoon-Texture Image Separation via a Global Treatment From Separation to Inpainting: A Global Approach Patch-Based Image Separation Patch-Based Image Inpainting Patch-Based Impulse Noise Removal Single Image Super-Resolution Single Image Super-Resolution: First Steps Single Image Super-Resolution: Detailed Algorithm Single Image Super-Resolution: The Overall Algorithm Single Image Super-Resolution: Results Summary Sparseland: What is it all About? Sparseland: What is Still Missing

Your Questions and Feedback

Administrative Issues Lets talk about: The Final and Bonus projects, along with all the quizzes should be submitted until next Thursday, January 24th 23:55. Next plans? You are required to present your research projects to me anytime between NOW and April 30th. The grades will be published soon after April 30th. No submission after this date will be permitted

That’s All We hope you enjoyed our course

The Convolutional Sparse Coding Model and Connections to Deep-Learning New Material? The Convolutional Sparse Coding Model and Connections to Deep-Learning

Feedback: Privacy Policy Feedback
Do Not Sell My Personal Information
About project: SlidePlayer Terms of Service

© 2025 SlidePlayer.com. Inc. All rights reserved.