Computational Intelligence based Hyperspectral Image Analysis and Applications, the second volume in this series, delves into the practical implementation of cutting-edge computational intelligence techniques in hyperspectral imaging, offering a comprehensive exploration of advanced analysis methods and their real-world applications. This volume consists 12 chapters that cover key topics such as classification, segmentation, pan sharpening and a variety of impactful applications. Readers will discover how these techniques are applied in fields like material identification, medical imaging, agriculture, wildfire detection, and remote sensing. This volume brings together an expert group of contributors, whose collective knowledge and practical experience offer readers a unique perspective on how to harness the power of computational intelligence for solving complex challenges in hyperspectral image analysis.

Essential resource demonstrating how hyperspectral image analysis can combine with computational intelligence techniqus focuses on applications in agriculture, environment, medical diagnostics, food and product inspection Recent research on Computational Intelligence based Hyperspectral Image Analysis

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Hyperspectral Imaging for the Diagnosis of Latent Tuberculosis Infection.- Hyperspectral Image Analysis for Plant Water Stress Assessment Using One-Dimensional Convolutional Neural Network.- Hyperspectral image synthesis from RGB images applied to wildfire detection.