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Machine learning and deep learning in energy systems: A review
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …
and decisive role in all of the sectors of society. To accelerate the process and improve the …
A comprehensive review on land use/land cover (LULC) change modeling for urban development: current status and future prospects
Land use land cover (LULC) modeling is considered as the best tool to comprehend and
unravel the dynamics of future urban expansion. The present paper provides a …
unravel the dynamics of future urban expansion. The present paper provides a …
ChangeMask: Deep multi-task encoder-transformer-decoder architecture for semantic change detection
Multi-temporal high spatial resolution earth observation makes it possible to detect complex
urban land surface changes, which is a significant and challenging task in remote sensing …
urban land surface changes, which is a significant and challenging task in remote sensing …
Time-series land cover change detection using deep learning-based temporal semantic segmentation
The process of sustainable urban development is accompanied by frequent and complex
land cover changes, and thus, clarify accurate information on land cover changes can …
land cover changes, and thus, clarify accurate information on land cover changes can …
Large-scale deep learning based binary and semantic change detection in ultra high resolution remote sensing imagery: From benchmark datasets to urban …
With the acceleration of urban expansion, urban change detection (UCD), as a significant
and effective approach, can provide the change information with respect to geospatial …
and effective approach, can provide the change information with respect to geospatial …
From single-to multi-modal remote sensing imagery interpretation: A survey and taxonomy
Modality is a source or form of information. Through various modal information, humans can
perceive the world from multiple perspectives. Simultaneously, the observation of remote …
perceive the world from multiple perspectives. Simultaneously, the observation of remote …
[HTML][HTML] Rising agricultural water scarcity in China is driven by expansion of irrigated cropland in water scarce regions
Increasing agricultural water scarcity is threatening food security and ecosystem
sustainability in China. Previous studies showed a deceleration in the growth of irrigation …
sustainability in China. Previous studies showed a deceleration in the growth of irrigation …
Semantic change detection using a hierarchical semantic graph interaction network from high-resolution remote sensing images
Current semantic change detection (SCD) methods face challenges in modeling temporal
correlations (TCs) between bitemporal semantic features and difference features. These …
correlations (TCs) between bitemporal semantic features and difference features. These …
Air quality predictions with a semi-supervised bidirectional LSTM neural network
L Zhang, P Liu, L Zhao, G Wang, W Zhang… - Atmospheric Pollution …, 2021 - Elsevier
Efficient and accurate air quality predictions can contribute to public health protection and
policy decision making. Fine particulate matter (PM 2.5) is an important index for measuring …
policy decision making. Fine particulate matter (PM 2.5) is an important index for measuring …
A large-scale change monitoring of wetlands using time series Landsat imagery on Google Earth Engine: a case study in Newfoundland
Wetlands across Canada have been, and continue to be, lost or altered under the influence
of both anthropogenic and natural activities. The ability to assess the rate of change to …
of both anthropogenic and natural activities. The ability to assess the rate of change to …