Search Tips
Our search has the following Google-type functionality:
+ (addition symbol)
If you use '+' at the start of a word, that word will be present in the search results.
eg. Harry +Potter
Search results will contain 'Potter'.
- (minus symbol)
If you use '-' at the start of a word, that word will be absent in the search results.
eg. Harry -Potter
Search results will not contain 'Potter'.
AND
If you use 'AND' between 2 words, then both those words will be present in the search results.
eg. Harry AND Potter
Search results will contain both 'Harry' and 'Potter'.
NOTE: AND will only work with single words not phrases.
OR
If you use 'OR' between 2 single words, then either or both of those words will be present in the search results.
eg. 'Harry OR Potter'
Search results will contain just 'Harry', or just 'Potter', or both 'Harry' and 'Potter'.
NOTE: OR will only work with single words not phrases.
NOT
If you use 'NOT' before a word, that word will be absent in the search results. (This is the same as using the minus symbol).
eg. 'Harry NOT Potter'
Search results will not contain 'Potter'.
NOTE: NOT will only work with single words not phrases.
" " (double quotation marks)
If you use double quotation marks around words, those words will be present in that order.
eg. "Harry Potter"
Search results will contain 'Harry Potter', but not 'Potter Harry'.
NOTE: "" cannot be combined with AND, OR & NOT searches.
* (asterisk)
If you use '*' in a word, it performs a wildcard search, as it signifies any number of characters. (Searches cannot start with a wildcard).
eg. 'Pot*er'
Search results will contain words starting with 'Pot' and ending in 'er', such as 'Potter'.
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Learning-Based Local Visual Representation and Indexing, reviews the state-of-the-art in visual content representation and indexing, introduces cutting-edge techniques in learning based visual representation, and discusses emerging topics in visual local representation, and introduces the most recent advances in content-based visual search techniques.
By: Rongrong Ji (Director of the Intelligent Multimedia Lab at Xiamen University), Yue Gao (Department of Automation, Tsinghua University, Beijing, China), Ling-Yu Duan (Peking University), Hongxun Yao (Harbin Institute of Technology, Harbin, China), Qionghai Dai (Deparment of Automation, Tsinghua University, Beijing, China)
Imprint: Morgan Kaufmann Publishers In
Country of Publication: United States
Dimensions: Height: 235mm, Width: 152mm, Spine: 8mm
Weight: 230g
ISBN: 9780128024096
ISBN 10: 0128024097
Series: Computer Science Reviews and Trends
Pages: 128
Publication Date: March 2015
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active
Chapter 1 Introduction Chapter 2 Context-aware semi-local feature detector Chapter 3 Unsupervised vocabulary optimization Chapter 4 Supervised vocabulary learning Chapter 5 3D Visual Descriptor Learning
Professor Rongrong Ji , is the Director of the Intelligent Multimedia Lab at Xiamen University. He is an active researcher pursuing innovations in multimedia, computer vision and pattern recognition. His scholarly work mainly focuses on building cutting-edge computer systems to understand visual scenes, to retrieve visual instances, and to digest human behaviors, with emerging applications to mobile visual search and social media analytics. His recent interests include compact visual descriptor, social media sentiment analysis, and holistic scene.He has served as the guest editor of IEEE MultiMedia Magazine, Neurocomputing, Signal Processing, ACM Multimedia Systems, and the Journal of Multimedia Tools and Applications. In addition he has served as the technical session chair at numerous conferences including, International Conference on Multimedia Retrieval 2014, Visual Communications and Image Processing 2013 and the 2012 Pacific-Rim Conference on Multimedia, etc. He has over 900 Citations and a Google Scholar h-index of 15. Yue Gao is with the Department of Automation, Tsinghua University. His recent research focuses on the areas of neuroimaging, multimedia and remote sensing. He is a senior member of IEEE. Qionghai Dai is with the Deparment of Automation, Tsinghua University. He has published more than 120 conference and journal papers, and holds 67 patents. His current research interests include the areas of computational photography, computational optical sensing, and compressed sensing imaging and vision. His work is motivated by challenging applications in the fields of computer vision, computer graphics, and robotics. He is a senior member of IEEE.
