最 低 价：￥691.56
定 价：￥768.40
作 者：HariSundaram，MilindNaphade，JohnSmith，Yong Rui 著 著
出 版 社：湖北辞书出版社
出版时间：2006-12-1
I S B N：9783540360186
| The LNCS series reports state-of-the-art results in computer science research,development,and education,at a high level and in both printed and electronic form.Enjoying tight cooperation with the R&D community,with numerous individuals,as well as with prestigious organizations and societies,LNCS has grown into the most comprehensive computer science resarch forum available. The scope of LNCS,including its subseries LNAI,spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields.The type of material publised traditionally includes. -proceedings(published in time for the respective conference) -post-proceedings(consisting of thoroughly revised final full papers) -research monographs(which may be basde on outstanding PhD work,research projects,technical reports,etc.). |
| Session O1: Interactive Image and Video Retrieval Interactive Experiments in Object-Based Retrieval Learned Lexicon-Driven Interactive Video Retrieval Mining Novice User Activity with TRECVID Interactive Retrieval Tasks Session 02: Semantic Image Retrieval A Linear-Algebraic Technique with an Application in Semantic Image Retrieval Logistic Regression of Generic Codebooks for Semantic Image Retrieval Query by Semantic Example Session 03: Visual Feature Analysis Corner Detectors for Affine Invariant Salient Regions: Is Color Important? Keyframe Retrieval by Keypoints: Can Point-to-Point Matching Help? Local Feature Trajectories for Efficient Event-Based Indexing of Video Sequences Session 04: Learning and Classification A Cascade of Unsupervised and Supervised Neural Networks for Natural Image Classification Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation Efficient Margin-Based Rank Learning Algorithms for Information Retrieval Session 05: Image and Video Retrieval Metrics Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure Video Clip Matching Using MPEG-7 Descriptors and Edit Distance Video Retrieval Using High Level Features: Exploiting Query Matching and Confidence-Based Weighting Session 06: Machine Tagging Annotating News Video with Locations Automatic Person Annotation of Family Photo Album Finding People Frequently Appearing in News Session P1: Poster Ⅰ A Novel Framework for Robust Annotation and Retrieval in Video Sequences …… Session P2：Poster Ⅱ Session A：ASU Special Session Session D：Demo Session Invited Talks Author Index |
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