Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In social communication, identifying facial expressions is a challenging and powerful task. Facial expression is used for non-verbal communication. Facial expressions recognition using machine learning techniques has many limitations, such as time complexity and lesser accuracy. So, to overcome the limitations of existing techniques convolutional neural network is introduced in this project which is a deep learning technique. A human being can respond to internal and external events using facial emotions or expressions in real-life scenarios. For video streaming, detecting human emotion and expression helps in the interaction between computers and humans. In this application, a convolutional neural network (CNN) is used for identifying facial expressions or emotions. The proposed CNN model for facial expression recognition outperforms the existing state of art methods such as support vector machine (SVM) and naïve Bayes (NB).
"FACIAL EMOTION RECOGNITION USING CONVOLUTION NEURAL NETWORK", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 5, page no.152 - 156, May-2023, Available :http://www.ijrti.org/papers/IJRTI2305022.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator