Advances in Machine Learning and Image Analysis for GeoAI

Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing, among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers, and more. This book provides graduate students, researchers, and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research.

Author: Saurabh Prasad, Jocelyn Chanussot, Jun Li

Publisher: Elsevier

Publication Date: Apr 03, 2024

Number of Pages: 364 pages

Language: English

Binding: Paperback

ISBN-10: 0443190771

ISBN-13: 9780443190773