Abstract: Leaf blast disease is a significant constraint in world-wide rice production systems, necessitating effective monitoring for optimized crop-yield management. Satellite-derived land-surface ...
Abstract: Classifying hyperspectral remote sensing images across different scenes has recently emerged as a significant challenge. When only historical labeled images (source domain, SD) are available ...
Abstract: Aerial image classification plays a vital role in applications such as building footprint extraction, water/soil analysis, 3D reconstruction. Accurate classification enables timely ...
Abstract: In recent years, uncrewed aerial vehicle (UAV) technology has shown great potential for application in hyperspectral image (HSI) classification tasks due to its advantages of flexible ...
Abstract: Chronic total occlusion (CTO) is a critical determinant of treatment efficacy in coronary artery disease, but its accurate diagnosis remains heavily reliant on the expertise of experienced ...
Abstract: In this article, we propose a lightweight privacy-preserving convolutional neural network (LPP-CNN) framework for military vehicle image classification. Existing target classification ...
Abstract: Background: Hyperspectral Image (HSI) classification involves analyzing images captured across numerous spectral bands to identify and categorize materials or objects. By exploiting spectral ...
EDITOR’S NOTE: Call to Earth is a CNN editorial series committed to reporting on the environmental challenges facing our planet, together with the solutions. Rolex’s Perpetual Planet Initiative has ...
Abstract: Deep learning models, especially hybrid models combining convolutional neural networks (CNN) and Transformer, introduce new ideas for hyperspectral image (HSI) classification. However, the ...
Most days, the country’s top newspapers have a wide range of photos gracing their front pages. But on Friday, every image topping the British front pages was identical: A snap of Andrew ...