[HTML][HTML] Ten deep learning techniques to address small data problems with remote sensing
A Safonova, G Ghazaryan, S Stiller… - International Journal of …, 2023 - Elsevier
Researchers and engineers have increasingly used Deep Learning (DL) for a variety of
Remote Sensing (RS) tasks. However, data from local observations or via ground truth is …
Remote Sensing (RS) tasks. However, data from local observations or via ground truth is …
Habitat quality evaluation and pattern simulation of coastal salt marsh wetlands
Y Huang, G Zheng, X Li, J ** with convolutional neural networks using Sentinel-2 images: case study of Rome
Land cover monitoring is crucial to understand land transformations at a global, regional and
local level, and the development of innovative methodologies is necessary in order to define …
local level, and the development of innovative methodologies is necessary in order to define …
[HTML][HTML] Multi-modality and multi-scale attention fusion network for land cover classification from VHR remote sensing images
Land cover classification from very high-resolution (VHR) remote sensing images is a
challenging task due to the complexity of geography scenes and the varying shape and size …
challenging task due to the complexity of geography scenes and the varying shape and size …
Performance analysis of deep convolutional autoencoders with different patch sizes for change detection from burnt areas
Fire is one of the primary sources of damages to natural environments globally. Estimates
show that approximately 4 million km2 of land burns yearly. Studies have shown that such …
show that approximately 4 million km2 of land burns yearly. Studies have shown that such …
[HTML][HTML] Spectral and spatial feature integrated ensemble learning method for grading urban river network water quality
X Zhou, C Liu, A Akbar, Y Xue, Y Zhou - Remote Sensing, 2021 - mdpi.com
Urban river networks have the characteristics of medium and micro scales, complex water
quality, rapid change, and time–space incoherence. Aiming to monitor the water quality …
quality, rapid change, and time–space incoherence. Aiming to monitor the water quality …
High spatial-resolution classification of urban surfaces using a deep learning method
Urban surface composition is key information for global carbon emission estimation,
mesoscale numerical simulations, and outdoor environment studies at both city and …
mesoscale numerical simulations, and outdoor environment studies at both city and …