Browsing Department of Applied Computer Science by Subject "Deep learning"
Now showing items 1-2 of 2
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A comprehensive review of 3D convolutional neural network-based classification techniques of diseased and defective crops using non-UAV-based hyperspectral images
(Elsevier B.V., 2023-09-14)Hyperspectral imaging (HSI) is a non-destructive and contactless technology that provides valuable information about the structure and composition of an object. It has the ability to capture detailed information about the ... -
A Deep Learning Framework: Land-Use/Land-Cover Mapping and Analysis using Multispectral Satellite Imagery
(Springer, 2019-07-17)In this article, we present an approach to land-use and land-cover (LULC) mapping from multispectral satellite images using deep learning methods. The terms satellite image classification and map production, although used ...