RADAM uses deep neural networks (CNNs) available in timm==0.6.7 for texture feature extraction, and then "classic" machine learning classification is done with scikit-learn classifiers. Several ...

Abstract: In urban scenes, there are man-made ground objects with complex structures and significant height differences, which leads to challenges in generating large-scale true digital orthophoto ...

An increasing number of rapid scoping, mapping reviews and evidence gap maps (‘Big Picture Reviews’ (BPRs)) are being undertaken to address broad research questions and provide an overview of a topic.

Disease development is often shaped by genetics, with how much or how little a gene is expressed influencing disease risk. While advances in technology and sequencing methods has led to a greater ...

Abstract: Accurately freespace detection is crucial to ensure the safe operation of autonomous vehicles. However, creating multi-scene datasets can be challenging. Mainstream research primarily ...