Graph Based Semi Supervised Learning In Computer Vision
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Graph Based Semi Supervised Learning
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Author : Amarnag Subramanya
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2014-07-01
Graph Based Semi Supervised Learning written by Amarnag Subramanya and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-01 with Computers categories.
While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a separate line of work, researchers have started to realize that graphs provide a natural way to represent data in a variety of domains. Graph-based SSL algorithms, which bring together these two lines of work, have been shown to outperform the state-of-the-art in many applications in speech processing, computer vision, natural language processing, and other areas of Artificial Intelligence. Recognizing this promising and emerging area of research, this synthesis lecture focuses on graph-based SSL algorithms (e.g., label propagation methods). Our hope is that after reading this book, the reader will walk away with the following: (1) an in-depth knowledge of the current state-of-the-art in graph-based SSL algorithms, and the ability to implement them; (2) the ability to decide on the suitability of graph-based SSL methods for a problem; and (3) familiarity with different applications where graph-based SSL methods have been successfully applied. Table of Contents: Introduction / Graph Construction / Learning and Inference / Scalability / Applications / Future Work / Bibliography / Authors' Biographies / Index
Graph Based Semi Supervised Learning In Computer Vision
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Author : Ning Huang
language : en
Publisher:
Release Date : 2009
Graph Based Semi Supervised Learning In Computer Vision written by Ning Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computer vision categories.
Machine learning from previous examples or knowledge is a key element in many image processing and pattern recognition tasks, e.g. clustering, segmentation, stereo matching, optical flow, tracking and object recognition. Acquiring that knowledge frequently requires human labeling of large data sets, which can be difficult and time-consuming to obtain. One way to ameliorate this task is to use Semi-supervised Learning (SSL), which combines both labeled and raw data and incorporates both global consistency (points in the same cluster are likely to have the same label) and local smoothness (nearby points are likely to have the same label). There are a number of vision tasks that can be solved efficiently and accurately using SSL. SSL has been applied extensively in clustering and image segmentation. In this dissertation, we will show that it is also suitable for stereo matching, optical flow and tracking problems. Our novel algorithm has converted the stereo matching problem into a multi-label semi-supervised learning one. It is similar to a diffusion process, and we will show our approach has a closed-form solution for the multi-label problem. It sparks a new direction from the traditional energy minimization approach, such as Graph Cut or Belief Propagation. The occlusion area is detected using the matching confidence level, and solved with local fitting. Our results have been applied in the Middlebury Stereo database, and are within the top 20 best results in terms of accuracy and is considerably faster than the competing approaches. We have also adapted our algorithm, and demonstrated its performance on optical flow problems. Again, our results are compared with the ground truth and state of the art on the Middlebury Flow database, and its advantages in accuracy as well as speed are demonstrated. The above algorithm is also being used in our current NSF sponsored project, an Automated, Real-Time Identification and Monitoring Instrument for Reef Fish Communities, whose goal is to track and recognize tropical fish, initially in an aquarium and ultimately on a coral reef. Our approach, which combines background subtraction and optical flow, automatically finds the correct outline of multiple fish species in the field of view, and tracks the contour reliably over consecutive frames. Currently, near real-time results are being achieved, with a processing frame rate of 3-5 fps. The recent progress in semi-supervised learning applied to image segmentation is also briefly reviewed.
Graph Based Semi Supervised Learning
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Author : Amarnag Subramanya
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Graph Based Semi Supervised Learning written by Amarnag Subramanya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a separate line of work, researchers have started to realize that graphs provide a natural way to represent data in a variety of domains. Graph-based SSL algorithms, which bring together these two lines of work, have been shown to outperform the state-of-the-art in many applications in speech processing, computer vision, natural language processing, and other areas of Artificial Intelligence. Recognizing this promising and emerging area of research, this synthesis lecture focuses on graph-based SSL algorithms (e.g., label propagation methods). Our hope is that after reading this book, the reader will walk away with the following: (1) an in-depth knowledge of the current state-of-the-art in graph-based SSL algorithms, and the ability to implement them; (2) the ability to decide on the suitability of graph-based SSL methods for a problem; and (3) familiarity with different applications where graph-based SSL methods have been successfully applied. Table of Contents: Introduction / Graph Construction / Learning and Inference / Scalability / Applications / Future Work / Bibliography / Authors' Biographies / Index
Computer Vision Eccv 2008
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Author : David Forsyth
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-07
Computer Vision Eccv 2008 written by David Forsyth and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-07 with Computers categories.
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Graph Based Representations In Pattern Recognition
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Author : Donatello Conte
language : en
Publisher: Springer
Release Date : 2019-06-10
Graph Based Representations In Pattern Recognition written by Donatello Conte and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This book constitutes the refereed proceedings of the 12th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2019, held in Tours, France, in June 2019. The 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. The papers discuss research results and applications at the intersection of pattern recognition, image analysis, and graph theory. They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.
Proceedings Of 2018 Chinese Intelligent Systems Conference
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Author : Yingmin Jia
language : en
Publisher: Springer
Release Date : 2018-10-06
Proceedings Of 2018 Chinese Intelligent Systems Conference written by Yingmin Jia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-06 with Technology & Engineering categories.
These proceedings present selected research papers from CISC’18, held in Wenzhou, China. The topics include Multi-Agent Systems, Networked Control Systems, Intelligent Robots, Complex System Theory and Swarm Behavior, Event-Triggered Control and Data-Driven Control, Robust and Adaptive Control, Big Data and Brain Science, Process Control, Nonlinear and Variable Structure Control, Intelligent Sensor and Detection Technology, Deep learning and Learning Control Guidance, Navigation and Control of Flight Vehicles, and so on. Engineers and researchers from academia, industry, and government can get an insight view of the solutions combining ideas from multiple disciplines in the field of intelligent systems.
Advances In Neural Information Processing Systems 19
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Author : Bernhard Schölkopf
language : en
Publisher: MIT Press
Release Date : 2007
Advances In Neural Information Processing Systems 19 written by Bernhard Schölkopf and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.
Semi Supervised Learning With Side Information
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Author : Yi Liu
language : en
Publisher:
Release Date : 2007
Semi Supervised Learning With Side Information written by Yi Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computer science categories.
Pattern Recognition
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Author : DAGM (Organization). Symposium
language : en
Publisher:
Release Date : 2004
Pattern Recognition written by DAGM (Organization). Symposium and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Image processing categories.
Advanced Materials And Computer Science
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Author : Garry Zhu
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2011-04-19
Advanced Materials And Computer Science written by Garry Zhu and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-19 with Technology & Engineering categories.
Selected, peer reviewed paper from 2011 International Conference on Advanced Materials and Computer Science (ICAMCS 2011), May 1-2, 2010 in Chengdu, China