INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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)
The challenge addressed in this project is the development of a comprehensive facial expression recognition system that encompasses three critical components: face
detection, facial feature extraction, and expression classification. This project aims
to automatically and accurately identify faces in images, extract and represent subtle changes in facial features corresponding to emotional expressions, and classify
these expressions, accounting for a range of emotions, including fundamental and
complex ones that may vary across cultures. When developing an automatic facial
expression recognition system, three primary challenges must be addressed: face detection, facial feature extraction, and expression classification. The core objective
of the project is to create a reliable and efficient framework for the classification of
facial expressions and to enable the system to discern and categorize these expressions with precision, encompassing a range of emotions from fundamental to complex, accounting for potential cross-cultural variations.The project operates within
the domain of Emotion Recognition and Analysis through Facial Expressions. It
is concerned with the development of a system that can automatically detect and
classify a wide range of emotional states by analyzing facial expressions. Diverse
dataset of facial images that depict a wide range of emotional states, including Sad,
Anger, Fear, Joy, Disgust, Confused and Surprise is gathered. An exceptional level
of accuracy, reaching 96%, has been achieved by the CNN (Convolutional Neural
Networks) algorithm in accurately identifying emotions.
Keywords:
Facial Expression Recognition, Face Detection, Facial Feature Extraction, Expression Classification, Diverse Datasets.
Cite Article:
"Mental health detection using facial emotion recognition", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 2, page no.b554-b593, February-2024, Available :http://www.ijnrd.org/papers/IJNRD2402169.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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