Zhenyu Huang^1,2, Gun Li², Xudong Sun¹, Yong Chen¹, Jie Sun¹, Zhangsong Ni^1,*, Yang Yang^1,*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3219-3238, 2023, DOI:10.32604/cmc.2023.039489

Abstract Onboard visual object tracking in unmanned aerial vehicles (UAVs) has attracted much interest due to its versatility. Meanwhile, due to high precision, Siamese networks are becoming hot spots in visual object tracking. However, most Siamese trackers fail to balance the tracking accuracy and time within onboard limited computational resources of UAVs. To meet the tracking precision and real-time requirements, this paper proposes a Siamese dense pixel-level network for UAV object tracking named SiamDPL. Specifically, the Siamese network extracts features of the search region and the template region through a parameter-shared backbone network, then performs correlation matching to obtain the candidate… More >

Jinxing Niu^1,*, Shaokui Gu¹, Junmin Du², Yongxing Hao¹

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2015-2031, 2023, DOI:10.32604/cmc.2023.040489

Abstract With the continuous development of the economy and society, plastic pollution in rivers, lakes, oceans, and other bodies of water is increasingly severe, posing a serious challenge to underwater ecosystems. Effective cleaning up of underwater litter by robots relies on accurately identifying and locating the plastic waste. However, it often causes significant challenges such as noise interference, low contrast, and blurred textures in underwater optical images. A weighted fusion-based algorithm for enhancing the quality of underwater images is proposed, which combines weighted logarithmic transformations, adaptive gamma correction, improved multi-scale Retinex (MSR) algorithm, and the contrast limited adaptive histogram equalization (CLAHE)… More >