Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter ...

Weed control is essential in apple orchards because weeds compete with trees for nutrients, water and sunlight, which can ...

As more nations and private companies turn their sights toward the Moon, the region between Earth and lunar orbit has become a frontier of opportunity, risk, and strategic competition. Now, the U.S.

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN integration. It improves dynamic lesion detection, temporal ...

Abstract: Deep learning-based object detection algorithms have achieved significant success in the field of computer vision. However, the wide range of target sizes in remote sensing images poses a ...

Scientists at Tarim University of China have proposed a way to address the challenging problem of pose recognition for photovoltaic panel cleaning robots. Their novel solution is based on a low power ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...

Maritime mobile edge computing (MMEC) technology facilitates the deployment of computationally intensive object detection tasks on Maritime Internet of Things (MIoT) devices with limited computing ...

Abstract: Underwater waste detection is a critical challenge for preserving aquatic ecosystems, particularly due to inherent underwater distortions such as light refraction, occlusion, and scattering.

Traditional manual detection of rural road surface distress is time-consuming and labor-intensive. In this paper, we propose a Mask R-CNN algorithm specifically designed for detecting rural road ...