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Computer Vision Beyond the Visible Spectrum
Details
Computer Vision is the area of Artificial Intelligence concerned with modelling and replicating human vision using computer software and hardware. Computer Vision is at the intersection of physiology, biology, psychology, computing and electronics, as it needs knowledge from all of these fields in order to understand and simulate the operation of the human vision system, including the eyes and relevant areas of the brain. This book brings together new research in this field and looks at how image-sensing devices have developed in recent years and how they are now used in a variety of commercial domains.
Presents pioneering new research in the area of Computer Vision Beyond the Visible Spectrum (CVBVS) that is taking place in both the commercial and military domains A timely publication as interest in this area of computer vision begins to grow
Inhalt
A Theoretical Framework for Predicting Performance of Object Recognition.- Methods for Improving the Performance of an SAR Recognition System.- Three-Dimensional Laser Radar Recognition Approaches.- Target Classification Using Adaptive Feature Extraction and Subspace Projection for Hyperspectral Imagery.- Moving Object Detection and Compression in IR Sequences.- Face Recognition in the Thermal Infrared.- Cardiovascular MR Image Analysis.- Visualization and Segmentation Techniques in 3D Ultrasound Images.- Time-Frequency Analysis in Terahertz-Pulsed Imaging.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09781849968874
- Auflage Softcover reprint of hardcover 1st edition 2005
- Editor Ioannis Pavlidis, Bir Bhanu
- Sprache Englisch
- Genre Anwendungs-Software
- Größe H235mm x B155mm x T19mm
- Jahr 2010
- EAN 9781849968874
- Format Kartonierter Einband
- ISBN 184996887X
- Veröffentlichung 21.10.2010
- Titel Computer Vision Beyond the Visible Spectrum
- Untertitel Advances in Pattern Recognition, Advances in Computer Vision and Pattern Recogni
- Gewicht 505g
- Herausgeber Springer London
- Anzahl Seiten 332
- Lesemotiv Verstehen