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  • Open Access

    ARTICLE

    Improving Real-Time Animal Detection Using Group Sparsity in YOLOv8: A Solution for Animal-Toy Differentiation

    Zia Ur Rehman1, Ahmad Syed2,*, Abu Tayab3, Ghanshyam G. Tejani4,5,*, Doaa Sami Khafaga6, El-Sayed M. El-kenawy7,8

    CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-25, 2026, DOI:10.32604/cmc.2025.070310 - 09 December 2025

    Abstract Object detection, a major challenge in computer vision and pattern recognition, plays a significant part in many applications, crossing artificial intelligence, face recognition, and autonomous driving. It involves focusing on identifying the detection, localization, and categorization of targets in images. A particularly important emerging task is distinguishing real animals from toy replicas in real-time, mostly for smart camera systems in both urban and natural environments. However, that difficult task is affected by factors such as showing angle, occlusion, light intensity, variations, and texture differences. To tackle these challenges, this paper recommends Group Sparse YOLOv8 (You… More >

  • Open Access

    ARTICLE

    A Disturbance Localization Method for Power System Based on Group Sparse Representation and Entropy Weight Method

    Zeyi Wang1, Mingxi Jiao1, Daliang Wang1, Minxu Liu1, Minglei Jiang2, He Wang3, Shiqiang Li3,*

    Energy Engineering, Vol.121, No.8, pp. 2275-2291, 2024, DOI:10.32604/ee.2024.028223 - 19 July 2024

    Abstract This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight method. Three different electrical quantities are selected as observations in the compressed sensing algorithm. The entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance levels. Subsequently, by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,… More >

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