Deep Learning and Computer Vision in Remote Sensing-II

Computer Vision (CV) have seen a massive rise in popularity in the remote sensing field over the last few years. This success is mostly due to the effectiveness of deep learning (DL) algorithms. However, remote sensing data acquisition and annotation, as well as information extraction from massive r...

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Bibliographic Details
Format:	Online
Language:	English
Published:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:	pose estimation landmark regression space target 1D landmark representation deep learning convolutional neural network (CNN) deep supervision lightweight model remote sensing semantic segmentation convolutional neural networks (CNNs) remote sensing images object detection knowledge inference module convolutional neural networks tree ensemble methods multi-label classification complex-valued U-Net complex-valued capsule network polarimetric synthetic aperture radar unmanned aerial vehicle (UAV) grassland grazing livestock remote sensing image artificial intelligence building extraction multi-scale object detection multi-feature fusion and attention network multi-branch convolution attention mechanism loss function remote-sensing image neural architecture search sparse regularization HRNet Earth observation land use and land cover classification transfer learning dynamic resolution adaptation small-object detection machine learning data augmentation automatic target recognition synthetic aperture radar spacecraft recognition few-shot feature adaptation generative family neural processes remote sensing imagery transformer Landsat thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science
Online Access:	ONIX_20231130_9783036593647_241
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ONIX_20231130_9783036593647_241

Deep Learning and Computer Vision in Remote Sensing-II

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