This paper presents a comprehensive evaluation of YOLO architectures for smoke and
wildfire detection, including YOLOv5, YOLOv6, YOLOv7, YOLOv8, and YOLO-NAS. We aim …

The semantic segmentation of land use and land cover (LULC) is a crucial and widely
employed remote sensing task. Conventional convolutional neural networks and vision …

Satellite remote sensing technology significantly contributes to intelligent transportation by
optimizing traffic planning via global perspectives and rich data, enhancing traffic efficiency …

Urban parks not only enhance urban ecology but also play a crucial role in providing cultural
ecosystem services (CESs) for the well-being of urban residents. Both artificial and natural …

With the continuous development of deep learning technology, object detection has
received extensive attention across various computer fields as a fundamental task of …

Synthetic aperture radar (SAR) image target detection methods based on semisupervised
learning, such as the mean teacher framework, have shown promise in diminishing the …

Object detection in remotely sensed (RS) satellite imagery has gained significance in smart
city concepts, which include urban planning, disaster management, and environmental …

Forests are essential for maintaining the ecological balance of the planet and providing
critical ecosystem services. Amidst an increasing rate of global forest loss due to various …

Developments in object detection algorithms are critical for urban planning, environmental
monitoring, surveillance, and many other applications. The primary objective of the article …

Submarine mud poses a risk to channel navigation safety. Traditional detection methods
lack efficiency and accuracy. As a result, this paper proposed an enhanced shallow …