This study is conducted in accordance with a systematic literature review (SLR) protocol.
SLR is tasked with finding publications, publishers, deep learning types, enhanced and …

Deep learning (DL) has emerged as a powerful technique for a wide range of computer
vision applications. Consequently, DL is also being adopted to process geospatial and …

To obtain reliable water segmentations from image data for real-time monitoring of river
water levels, a comparison of 32 convolutional neural networks was performed. They were …

High-resolution remote sensing images have become mainstream remote sensing data, but
there is an obvious" salt and pepper phenomenon" in the existing semantic segmentation …

The utilization of renewable energy is an essential way to address climate change and
achieve “carbon neutrality”. As one of the most promising strategies for energy development …

To manage the rumors in social media to reduce the harm of rumors in society. Many studies
used methods of deep learning to detect rumors in open networks. To comprehensively sort …

A point-of-interest (POI) represents a specific point location that may be useful or interesting
for people, and therefore, each and every building footprint in a topographic map can be …

Automatically extract lake water bodies of optical remote sensing images is a very
challenging task, because there are many small lakes in such images, these small lakes …

This paper examines the potential of Human-Centered AI (HCAI) solutions to support
radiologists in diagnosing prostate cancer. Prostate cancer is one of the most prevalent and …

Semantic segmentation with deep learning networks has become an important approach to
the extraction of objects from very high-resolution remote sensing images. Vision …