Data Fusion: Concepts and Ideas [electronic resource] /by H B Mitchell.
by Mitchell, H B [author.]; SpringerLink (Online service).
Material type:
BookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2012.Edition: 2nd ed. 2012.Description: XIV, 346p. online resource.ISBN: 9783642272226.Subject(s): Engineering | Electronics | Engineering | Signal, Image and Speech Processing | Computational Intelligence | Electronics and Microelectronics, InstrumentationDDC classification: 621.382 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| TA1637-1638 (Browse shelf) | Available | ||||
| TK7882.S65 (Browse shelf) | Available | ||||
| Long Loan | MAIN LIBRARY | TK5102.9 (Browse shelf) | Available |
Close shelf browser
| Q334-342 Advanced Agent Technology | TJ210.2-211.495 Advanced Agent Technology | TA345-345.5 Empowering Open and Collaborative Governance | TA1637-1638 Data Fusion: Concepts and Ideas | QA276-280 Bayesian Methods in Structural Bioinformatics | RK529-535 Clinical Facial Analysis | RC254-282 Nutritional Management of Cancer Treatment Effects |
Introduction -- Sensors -- Architecture -- Common Representational Format -- Spatial Alignment -- Temporal Alignment -- Semantic Alignment -- Radiometric Normalization -- Bayesian Inference -- Parameter Estimation -- Robust Statistics -- Sequential Bayesian Inference -- Bayesian Decision Theory -- Ensemble Learning -- Sensor Management.
“Data Fusion: Concepts and Ideas” provides a comprehensive introduction to the concepts and idea of multisensor data fusion. This textbook is an extensively revised second edition of the author's successful book: "Multi-Sensor Data Fusion: An Introduction". The book is self-contained and no previous knowledge of multi-sensor data fusion is assumed. The reader is made familiar with tools taken from a wide range of diverse subjects including: neural networks, signal processing, statistical estimation, tracking algorithms, computer vision and control theory which are combined by using a common statistical framework. As a consequence, the underlying pattern of relationships that exists between the different methodologies is made evident. The book is illustrated with many real-life examples taken from a diverse range of applications and contains an extensive list of modern references. The new completely revised and updated edition includes nearly 70 pages of new material including a full new chapter as well as approximately 30 new sections, 50 new examples and 100 new references as well as additional Matlab code where appropriate.
There are no comments for this item.