Advanced Machine Learning and Deep Learning Approaches for Remote Sensing

This reprint provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These technique...

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Detalhes bibliográficos
Formato:	Online
Idioma:	inglês
Publicado em:	MDPI - Multidisciplinary Digital Publishing Institute 2023
Assuntos:	live fuel moisture content deep learning ensemble learning multi-source remote sensing spatiotemporal fusion dilated convolution improved transformer encoder global correlation information semantic segmentation attention mechanism robust deep learning remote sensing data fusion low-light image enhancement retinex theory remote-sensing orbital angular momentum mode detection fine-grained image classification attention pyramid atmospheric turbulence sea surface temperature mutual information LSTM self-attention interdimensional attention noise suppression deblurring curriculum learning image reconstruction turbulence degradation depthwise separable convolutional neural networks spectrogram augmentation sound detection vehicle detection image super-resolution model design evaluation methods maritime communication evaporation duct multi-dimensional prediction model digital surface model multimodal multi-scale supervision feature separation reconstruction refinement significant wave height autoencoder principal component analysis SAR altimeter Gaussian process regression convolutional neural network computer vision solar farm solar panel capacity estimation photovoltaics optical remote sensing peri-urban forests lightweight convolutional neural network FlexibleNet carbon sequestration semi-supervised learning few-shot learning SAR target recognition discriminative representation learning remote image CNN multiscale feature fusion Transformer improved Tversky loss two-step convolution model cloud detection cloud matting cloud removal n/a thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography
Acesso em linha:	ONIX_20230714_9783036579467_85
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Descrição
Resumo:	This reprint provides research on how technologies such as artificial intelligence-based machine learning and deep learning can be applied to remote sensing. Through this, we can see the process of solving the existing problems of image and image signal processing for remote sensing. These techniques are computationally intensive and require the help of high-performance computing devices. With the development of devices such as GPUs, remote sensing technology, and aerial sensing technology, it is possible to monitor the Earth with high-resolution images and to obtain vast amounts of Earth observation data. The papers published in this reprint describe recent advances in big data processing and artificial intelligence-based technologies for remote sensing technology.

Advanced Machine Learning and Deep Learning Approaches for Remote Sensing

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