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MobilityDL: A Review of Deep Learning From Trajectory Data
Trajectory data combines the complexities of time series, spatial data, and (sometimes irrational) movement behavior.
Landslide Detection and Segmentation Using Remote Sensing Images and Deep Neural Network
Finally, we propose a combined loss function which leverages Focal loss and IoU loss to train the network.
A Light-weight Deep Learning Model for Remote Sensing Image Classification
In this paper, we present a high-performance and light-weight deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the aerial scene of a remote sensing image.
Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network
The task of remote sensing image scene classification (RSISC), which aims at classifying remote sensing images into groups of semantic categories based on their contents, has taken the important role in a wide range of applications such as urban planning, natural hazards detection, environment monitoring, vegetation mapping, or geospatial object detection.
