Muhammad Aliff Haiqal Darmawan¹, Shahrul Nizan Abd Mukti², Khairul Nizam Tahar^1,*

Revue Internationale de Géomatique, Vol.34, pp. 21-35, 2025, DOI:10.32604/rig.2024.057266 - 13 January 2025

Abstract Potholes are the most prevalent type of structural defect found on roads, caused by aging infrastructure, heavy rains, heavy traffic, thin or weak substructures, and other factors. Regular assessment of road conditions is essential for maintaining and improving road networks. Current techniques for identifying potholes on urban roadways primarily rely on public reporting, such as hotlines or social networking websites, which are both time-consuming and inefficient. This study aims to detect potholes using Unmanned Aerial Vehicles (UAVs) images, enabling accurate analysis of their size, shape, and location, thereby enhancing detection efficiency compared to conventional methods.… More >

Zenglun Guan^1,2, Murad S. Alfarzaeai^1,3,*, Eryi Hu^1,3,*, Taqiaden Alshmeri⁴, Wang Peng³

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 279-306, 2024, DOI:10.32604/cmc.2024.047159 - 25 April 2024

Abstract In the coal mining industry, the gangue separation phase imposes a key challenge due to the high visual similarity between coal and gangue. Recently, separation methods have become more intelligent and efficient, using new technologies and applying different features for recognition. One such method exploits the difference in substance density, leading to excellent coal/gangue recognition. Therefore, this study uses density differences to distinguish coal from gangue by performing volume prediction on the samples. Our training samples maintain a record of 3-side images as input, volume, and weight as the ground truth for the classification. The… More >