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An optimized facial recognition model for identifying criminal activities using deep learning strategy

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Abstract

The most important research field in the current period is facial recognition and detection. Furthermore, facial expression recognition applications are essential in various research areas such as criminal investigation, security, data base management systems (DBMS), innovative card application, and video surveillance systems. A criminal investigation is an important area of study. Thus, in today’s world, crime activities are fast expanding in response to psychological trauma. As a result, applying deep learning (DL) algorithms for face expression identification and crime activity monitoring is a growing area of investigation. In terms of pre-processing, feature extraction, and recognizing diverse facial emotions, DL produces better results. As a result, the current study seeks to offer a revolutionary intelligent Strawberry-based convolution neural network (SbCNN). When applied to the Kaggle face expression database, the created SbCNN technique performed best. Face verification and criminal face detection can be accomplished using this approach and the optimization fitness function. Even though the established design improves the robustness of feature extraction and classification, it is a time-consuming process.

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Data sharing is not applicable to this article as no new data were created or analyzed in this study.

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Authors and Affiliations

  1. Artificial Intelligence Laboratory, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    S. Gokulakrishnan

  2. Deputy Provost, ITM SLS Baroda University, Vadodara, Gujarat, India

    Prasun Chakrabarti

  3. Artificial Intelligence Laboratory, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Bui Thanh Hung

  4. Department of Computer Science and Engineering, KG Reddy College of Engineering and Technology (Autonomous), Hyderabad, Telangana, India

    S. Siva Shankar

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  1. S. Gokulakrishnan
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  2. Prasun Chakrabarti
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  3. Bui Thanh Hung
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  4. S. Siva Shankar
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Correspondence to S. Gokulakrishnan.

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Gokulakrishnan, S., Chakrabarti, P., Hung, B.T. et al. An optimized facial recognition model for identifying criminal activities using deep learning strategy. Int. j. inf. tecnol. 15, 3907–3921 (2023). https://doi.org/10.1007/s41870-023-01420-6

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