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Hyperspectral Image Analysis Advances in Machine Learning and Signal Processing

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. It presents advances in deep learning, multiple instance le...

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Bibliographic Details
Other Authors: Prasad, Saurabh (Editor), Chanussot, Jocelyn (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2020, 2020
Edition:1st ed. 2020
Series:Advances in Computer Vision and Pattern Recognition
Subjects:
Geographical Information System
Computer Vision
Artificial Intelligence
Signal, Speech And Image Processing
Geographic Information Systems
Signal Processing
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • 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

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