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Title: :  Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning
PaperId: :  22567
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 1 2024
DUI:    16.0415/IJARIIE-22567
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
RITHIKAA KBANNARI AMMAN INSTITUTE OF TECHNOLOGY
KISHORE V BANNARI AMMAN INSTITUTE OF TECHNOLOGY
MR.SATHEESH N PBANNARI AMMAN INSTITUTE OF TECHNOLOGY

Abstract

COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY
DEEP LEARNING, FACIAL RECOGNITION, CONVOLUTIONAL NEURAL NETWORK, STRESS DETECTION ,OPENCV
This paper endeavours to increase a actual-time facial reputation gadget for non-intrusive pressure detection utilizing the synergies of opencv and deep analyzing methodologies the primary aim is to create a precise and inexperienced device that respects patron consolation while empowering individuals with immediately stress manage competencies the devices objectives encompass because it must be detecting strain tiers via facial popularity enforcing actual-time facial picture seize thru the use of a web virtual digital camera leveraging opencvs haar cascade for strong face detection and integrating a pre-knowledgeable convolutional neural network cnn model for strain estimation the proposed work consists of shooting facial pictures thru an internet digital camera making use of opencvs haar cascade for face detection and processing remoted faces with a meticulously skilled cnn model this --step technique complements the accuracy of pressure diploma checks via figuring out nuanced facial cues indicative of stress the ensuing gadget stands at the intersection of pc innovative prescient and intellectual health technology presenting a bendy and mighty solution for pressure monitoring and nicely-being projects this system addresses the crucial issue of real-time stress detection the usage of non-invasive techniques pressure is a challenge in cutting-edge existence exacerbated by means of elements consisting of the covid pandemic the assignment is steady with the findings of the literature review which emphasize the significance of non-invasive pressure detection strategies including imaging strategies the proposed real-time face reputation algorithm sticks out by combining the talents of opencv with deep learning the opencv haar cascade improves face popularity while the mixed cnn model will increase the accuracy of pressure estimation an emphasis on consolation as a consumer makes the device non-intrusive and respectful of person privacy the literature assessment well-knownshows various techniques for stress detection along with picture-primarily based biosignal machine gaining knowledge of with face masks and deep gaining knowledge of with defeat cascade algorithms these research provide insights precious in phrases of the processes and demanding situations associated with stress popularity the significance of the program extends beyond technological innovation aiming to help boost attention of mental health and nicely-being by supplying people with on the spot strain remedy this system aligns with the wider goal of enhancing intellectual fitness thru era in end the real-time facial recognition assignment for non-invasive human strain detection combines contemporary era with a holistic approach to deal with an important thing of human nicely-being thru diligent implementation and pursuit of specific targets the venture aims to have a significant impact on strategies of strain detection pc imaginative and prescient and mental health technologies

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IJARIIE RITHIKAA K, KISHORE V , and MR.SATHEESH N P. "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 1 2024 Page 1154-1159
MLA RITHIKAA K, KISHORE V , and MR.SATHEESH N P. "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning." International Journal Of Advance Research And Innovative Ideas In Education 10.1(2024) : 1154-1159.
APA RITHIKAA K, KISHORE V , & MR.SATHEESH N P. (2024). Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning. International Journal Of Advance Research And Innovative Ideas In Education, 10(1), 1154-1159.
Chicago RITHIKAA K, KISHORE V , and MR.SATHEESH N P. "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 1 (2024) : 1154-1159.
Oxford RITHIKAA K, KISHORE V , and MR.SATHEESH N P. 'Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 1, 2024, p. 1154-1159. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Real_Time_Facial_Recognition_for_Non_Intrusive_Human_Stress_Detection_using_OpenCV_and_Deep_Learning_ijariie22567.pdf (Accessed : 13 February 2024).
Harvard RITHIKAA K, KISHORE V , and MR.SATHEESH N P. (2024) 'Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning', International Journal Of Advance Research And Innovative Ideas In Education, 10(1), pp. 1154-1159IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Real_Time_Facial_Recognition_for_Non_Intrusive_Human_Stress_Detection_using_OpenCV_and_Deep_Learning_ijariie22567.pdf (Accessed : 13 February 2024)
IEEE RITHIKAA K, KISHORE V , and MR.SATHEESH N P, "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 1, pp. 1154-1159, Jan-Feb 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/Real_Time_Facial_Recognition_for_Non_Intrusive_Human_Stress_Detection_using_OpenCV_and_Deep_Learning_ijariie22567.pdf [Accessed : 13 February 2024].
Turabian RITHIKAA K, KISHORE V , and MR.SATHEESH N P. "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 1 (13 February 2024).
Vancouver RITHIKAA K, KISHORE V , and MR.SATHEESH N P. Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : 13 February 2024]; 10(1) : 1154-1159. Available from: https://ijariie.com/AdminUploadPdf/Real_Time_Facial_Recognition_for_Non_Intrusive_Human_Stress_Detection_using_OpenCV_and_Deep_Learning_ijariie22567.pdf
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