CONTEXT AGGREGATION NETWORK FOR SEMANTIC LABELING IN AERIAL IMAGES

Semantic labeling for high resolution aerial images is a fundamental and necessary task in remote sensing image analysis.It is widely used in land-use surveys, change jolly rancher filled gummies detection, and environmental protection.Recent researches reveal the superiority of Convolutional Neural Networks (CNNs) in this task.However, multi-scale

Seismic activity prediction has been a challenging research domain: in this regard, accurate prediction using historical data is an intricate task.Numerous machine learning and traditional approaches have been presented lately for seismic activity prediction; however, no generalizable model exists.In this work, we consider seismic activity predicat