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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 120
Article Submitted : 24205
Article Published : 9239
Total Authors : 24597
Total Reviewer : 847
Total Countries : 165
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Published Paper Details
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| Paper Title: | Human Face Recognition of Emotion using Deep Learning |
| Authors Name: | Kuldeep Sahu , Sujal nandi , Jayprakash Devangan , Prabhakar Sharma |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_211775
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| Published Paper Id: | IJRTI2604259 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | Abstract—Face Emotion Detection is an intelligent face detection system. classifying human emotions on the basis of facial expressions on a deep basis. learning techniques. The goal of the project is to advance human– computer interaction, whereby machines are able to identify the emotional state of a person in real-time. It uses computer vision and convolutional neural networks (CNNs) to examine the facial characteristics of. pictures or video livestreams. System is trained using labelled dataset. such as happiness, Sadness, Anger, Surprise, Fear etc. To start with, there are cleanup procedures that pictures undergo - faces are identi-fied, adjusted to the right. size, flattened, became number grids to teach machines. Then an intelligent system learns those face shots that have been fixed, gathering small hints that are related to such emotions as joy or anger. When the learning part finishes, it begins to guess moods out of new pictures or live camera streams. Python does the brainwork on the inside: running tests, making predictions, keeping things running on the backburner. the scenes. On the front people can see a neat display of results. as they happen. A possible use of this arrangement is by monitor-ing emotions during therapy sessions. Computers are more re-sponsive to emotions they spot right, indicating machines are able to pick up on mood cues. Another spot it fits? Classes in which technology accommodates students with difficulty. |
| Keywords: | Keywords—Facial Emotion Recognition, CNN, Deep Learning, Computer Vision, Real-Time Detection. |
| Cite Article: | "Human Face Recognition of Emotion using Deep Learning ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b890-b899, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604259.pdf |
| Downloads: | 000205504 |
| 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 |
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Published Paper ID: IJRTI2604259
Registration ID:211775
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b890-b899 Country: Raipur, Chhattisgarh, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604259 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604259 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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