Hyperspectral Image Analysis

Advances in Machine Learning and Signal Processing

AvSaurabh Prasad,Jocelyn Chanussot

Häftad, Engelska, 2021

Del i serien Advances in Computer Vision and Pattern Recognition

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Beskrivning

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding.

Produktinformation

Utgivningsdatum:2021-04-29
Mått:155 x 235 x undefined mm
Format:Häftad
Språk:Engelska
Serie:Advances in Computer Vision and Pattern Recognition
Antal sidor:466
Förlag:Springer Nature Switzerland AG
ISBN:9783030386191

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Mer om författaren

Dr. Saurabh Prasad is an Associate Professor at the Department of Electrical and Computer Engineering at the University of Houston, TX, USA.Dr. Jocelyn Chanussot is a Professor in the Signal and Images Department at Grenoble Institute of Technology, France.

Innehållsförteckning

1. Introduction.- 2. Machine Learning Methods for Spatial and Temporal Parameter Estimation.- 3. Deep Learning for Hyperspectral Image Analysis, Part I: Theory and Algorithms.- 4. Deep Learning for Hyperspectral Image Analysis, Part II: Applications to Remote Sensing and Biomedicine.- 5. Advances in Deep Learning for Hyperspectral Image Analysis - Addressing Challenges Arising in Practical Imaging Scenarios.- 6. Addressing the Inevitable Imprecision: Multiple Instance Learning for Hyperspectral Image Analysis.