Advanced Deep Learning Strategies for the Analysis of Remote Sensing Images

• その他の著者: Bazi, Yakoub (編集者), Pasolli, Edoardo (編集者)
• フォーマット: 電子媒体 図書の章
• 言語: 英語
• 出版事項: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• 主題: Research & information: general; synthetic aperture radar; despeckling; multi-scale; LSTM; sub-pixel; high-resolution remote sensing imagery; road extraction; machine learning; DenseUNet; scene classification; lifting scheme; convolution; CNN; image classification; deep features; hand-crafted features; Sinkhorn loss; remote sensing; text image matching; triplet networks; EfficientNets; LSTM network; convolutional neural network; water identification; water index; semantic segmentation; high-resolution remote sensing image; pixel-wise classification; result correction; conditional random field (CRF); satellite; object detection; neural networks; single-shot; deep learning; global convolution network; feature fusion; depthwise atrous convolution; high-resolution representations; ISPRS vaihingen; Landsat-8; faster region-based convolutional neural network (FRCNN); single-shot multibox detector (SSD); super-resolution; remote sensing imagery; edge enhancement; satellites; open-set domain adaptation; adversarial learning; min-max entropy; pareto ranking; SAR; Sentinel-1; Open Street Map; U-Net; desert; road; infrastructure; mapping; monitoring; deep convolutional networks; outline extraction; misalignments; nearest feature selector; hyperspectral image classification; two stream residual network; Batch Normalization; plant disease detection; precision agriculture; UAV multispectral images; orthophotos registration; 3D information; orthophotos segmentation; wildfire detection; convolutional neural networks; densenet; generative adversarial networks; CycleGAN; data augmentation; pavement markings; visibility; framework; urban forests; OUDN algorithm; object-based; high spatial resolution remote sensing; Generative Adversarial Networks; post-disaster; building damage assessment; anomaly detection; Unmanned Aerial Vehicles (UAV); xBD; feature engineering; orthophoto; unsupervised segmentation
• オンライン･アクセス: DOAB: download the publication; DOAB: description of the publication

The rapid growth of the world population has resulted in an exponential expansion of both urban and agricultural areas. Identifying and managing such earthly changes in an automatic way poses a worth-addressing challenge, in which remote sensing technology can have a fundamental role to answer-at le...