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  • Open Access

    ARTICLE

    Faster Region Convolutional Neural Network (FRCNN) Based Facial Emotion Recognition

    J. Sheril Angel1, A. Diana Andrushia1,*, T. Mary Neebha1, Oussama Accouche2, Louai Saker2, N. Anand3

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2427-2448, 2024, DOI:10.32604/cmc.2024.047326

    Abstract Facial emotion recognition (FER) has become a focal point of research due to its widespread applications, ranging from human-computer interaction to affective computing. While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets, recent strides in artificial intelligence and deep learning (DL) have ushered in more sophisticated approaches. The research aims to develop a FER system using a Faster Region Convolutional Neural Network (FRCNN) and design a specialized FRCNN architecture tailored for facial emotion recognition, leveraging its ability to capture spatial hierarchies within localized regions of facial… More >

  • Open Access

    ARTICLE

    Facial Action Coding and Hybrid Deep Learning Architectures for Autism Detection

    A. Saranya1,*, R. Anandan2

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1167-1182, 2022, DOI:10.32604/iasc.2022.023445

    Abstract Hereditary Autism Spectrum Disorder (ASD) is a neuron disorder that affects a person's ability for communication, interaction, and also behaviors. Diagnostics of autism are available throughout all stages of life, from infancy through adolescence and adulthood. Facial Emotions detection is considered to be the most parameter for the detection of Autismdisorders among the different categories of people. Propelled with a machine and deep learning algorithms, detection of autism disorder using facial emotions has reached a new dimension and has even been considered as the precautionary warning system for caregivers. Since Facial emotions are limited to… More >

  • Open Access

    ARTICLE

    AI Cannot Understand Memes: Experiments with OCR and Facial Emotions

    Ishaani Priyadarshini*, Chase Cotton

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 781-800, 2022, DOI:10.32604/cmc.2022.019284

    Abstract

    The increasing capabilities of Artificial Intelligence (AI), has led researchers and visionaries to think in the direction of machines outperforming humans by gaining intelligence equal to or greater than humans, which may not always have a positive impact on the society. AI gone rogue, and Technological Singularity are major concerns in academia as well as the industry. It is necessary to identify the limitations of machines and analyze their incompetence, which could draw a line between human and machine intelligence. Internet memes are an amalgam of pictures, videos, underlying messages, ideas, sentiments, humor, and experiences,

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