Computer Vision Beyond the Visible Spectrum
Bhanu, Bir.
Computer Vision Beyond the Visible Spectrum [electronic resource] / edited by Bir Bhanu, Ioannis Pavlidis. - X, 320 p. 156 illus., 5 illus. in color. online resource. - Advances in Pattern Recognition . - Advances in Pattern Recognition .
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.
Recently, there has been a dramatic increase in the use of sensors in the non-visible bands. As a result, there is a need for existing computer vision methods and algorithms to be adapted for use with non-visible sensors, or for the development of completely new methods and systems. Computer Vision Beyond the Visible Spectrum is the first book to bring together state-of-the-art work in this area. It presents new & pioneering research across the electromagnetic spectrum in the military, commercial, and medical domains. By providing a detailed examination of each of these areas, it focuses on the development of state-of-the-art algorithms and looks at how they can be used to solve existing & new challenges within computer vision. Essential reading for academics & industrial researchers working in the area of computer vision, image processing, and medical imaging, it will also be useful background reading for advanced undergraduate & postgraduate students.
9781846280658
10.1007/b138155 doi
Computer science.
Neurosciences.
Artificial intelligence.
Computer graphics.
Computer vision.
Optical pattern recognition.
Computer Science.
Computer Graphics.
Image Processing and Computer Vision.
Pattern Recognition.
Artificial Intelligence (incl. Robotics).
Electronic and Computer Engineering.
Neurosciences.
T385
006.6
Computer Vision Beyond the Visible Spectrum [electronic resource] / edited by Bir Bhanu, Ioannis Pavlidis. - X, 320 p. 156 illus., 5 illus. in color. online resource. - Advances in Pattern Recognition . - Advances in Pattern Recognition .
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.
Recently, there has been a dramatic increase in the use of sensors in the non-visible bands. As a result, there is a need for existing computer vision methods and algorithms to be adapted for use with non-visible sensors, or for the development of completely new methods and systems. Computer Vision Beyond the Visible Spectrum is the first book to bring together state-of-the-art work in this area. It presents new & pioneering research across the electromagnetic spectrum in the military, commercial, and medical domains. By providing a detailed examination of each of these areas, it focuses on the development of state-of-the-art algorithms and looks at how they can be used to solve existing & new challenges within computer vision. Essential reading for academics & industrial researchers working in the area of computer vision, image processing, and medical imaging, it will also be useful background reading for advanced undergraduate & postgraduate students.
9781846280658
10.1007/b138155 doi
Computer science.
Neurosciences.
Artificial intelligence.
Computer graphics.
Computer vision.
Optical pattern recognition.
Computer Science.
Computer Graphics.
Image Processing and Computer Vision.
Pattern Recognition.
Artificial Intelligence (incl. Robotics).
Electronic and Computer Engineering.
Neurosciences.
T385
006.6