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Opis

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.Advances in Machine Learning and Image Analysis for GeoAI 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. Covers the latest machine learning and signal processing techniques that can effectively leverage geospatial imagery at scaleChapters cover a variety of algorithmic frameworks including variants of convolutional neural networks, multi-stream networks, Bayesian networks and moreIncludes open-source code-base for algorithms described in each chapter

Szczegóły książki

Kategoria Książki po angielsku Earth sciences, geography, environment, planning Earth sciences

• Pełny tytuł: Advances in Machine Learning and Image Analysis for GeoAI
• Autor: Saurabh Prasad, Jocelyn Chanussot, Jun Li
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 350
• EAN: 9780443190773
• ISBN: 0443190771
• ID: 43896519
• Wymiary: 229 × 151 mm
• Data wydania: 01. April 2024

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