Bing Shi^1,*, Jianhua Zhao¹, Bin Ma¹, Juan Huan², Yueping Sun³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2437-2456, 2024, DOI:10.32604/cmc.2024.056377 - 18 November 2024

Abstract Real-time detection of unhealthy fish remains a significant challenge in intensive recirculating aquaculture. Early recognition of unhealthy fish and the implementation of appropriate treatment measures are crucial for preventing the spread of diseases and minimizing economic losses. To address this issue, an improved algorithm based on the You Only Look Once v5s (YOLOv5s) lightweight model has been proposed. This enhanced model incorporates a faster lightweight structure and a new Convolutional Block Attention Module (CBAM) to achieve high recognition accuracy. Furthermore, the model introduces the α-SIoU loss function, which combines the α-Intersection over Union (α-IoU) and… More >

Mesfer Al Duhayyim¹, Haya Mesfer Alshahrani², Fahd N. Al-Wesabi³, Mohammed Alamgeer⁴, Anwer Mustafa Hilal^5,*, Manar Ahmed Hamza⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5871-5887, 2022, DOI:10.32604/cmc.2022.021093 - 11 October 2021

Abstract An exponential growth in advanced technologies has resulted in the exploration of Ocean spaces. It has paved the way for new opportunities that can address questions relevant to diversity, uniqueness, and difficulty of marine life. Underwater Wireless Sensor Networks (UWSNs) are widely used to leverage such opportunities while these networks include a set of vehicles and sensors to monitor the environmental conditions. In this scenario, it is fascinating to design an automated fish detection technique with the help of underwater videos and computer vision techniques so as to estimate and monitor fish biomass in water… More >