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  • Open Access

    ARTICLE

    Squirrel Search Optimization with Deep Convolutional Neural Network for Human Pose Estimation

    K. Ishwarya, A. Alice Nithya*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6081-6099, 2023, DOI:10.32604/cmc.2023.034654

    Abstract Human pose estimation (HPE) is a procedure for determining the structure of the body pose and it is considered a challenging issue in the computer vision (CV) communities. HPE finds its applications in several fields namely activity recognition and human-computer interface. Despite the benefits of HPE, it is still a challenging process due to the variations in visual appearances, lighting, occlusions, dimensionality, etc. To resolve these issues, this paper presents a squirrel search optimization with a deep convolutional neural network for HPE (SSDCNN-HPE) technique. The major intention of the SSDCNN-HPE technique is to identify the human pose accurately and efficiently.… More >

  • Open Access

    ARTICLE

    Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets

    Doaa Sami Khafaga1, El-Sayed M. El-kenawy2, Fadwa Alrowais1,*, Sunil Kumar3, Abdelhameed Ibrahim4, Abdelaziz A. Abdelhamid5,6

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4027-4041, 2023, DOI:10.32604/cmc.2023.033039

    Abstract In data mining and machine learning, feature selection is a critical part of the process of selecting the optimal subset of features based on the target data. There are 2n potential feature subsets for every n features in a dataset, making it difficult to pick the best set of features using standard approaches. Consequently, in this research, a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm (ASSOA) has been proposed. When using metaheuristics to pick features, it is common for the selection of features to vary across runs, which can lead to instability. Because of… More >

  • Open Access

    ARTICLE

    A Robust Video Watermarking Scheme with Squirrel Search Algorithm

    Aman Bhaskar1, Chirag Sharma1, Khalid Mohiuddin2, Aman Singh1,*, Osman A. Nasr2, Mamdooh Alwetaishi3

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3069-3089, 2022, DOI:10.32604/cmc.2022.019866

    Abstract Advancement in multimedia technology has resulted in protection against distortion, modification, and piracy. For implementing such protection, we have an existing technique called watermarking but obtaining desired distortion level with sufficient robustness is a challenging task for watermarking in multimedia applications. In the paper, we proposed a smart technique for video watermarking associating meta-heuristic algorithms along with an embedding method to gain an optimized efficiency. The main aim of the optimization algorithm is to obtain solutions with maximum robustness, and which should not exceed the set threshold of quality. To represent the accuracy of the proposed scheme, we employ a… More >

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