Stress Sense: Enhanced Stress Detection and Management Via Image Processing

Gowtham. J.; Hariprasanth. T; Janaki. V; Kaviya.S; Sindhuri.P1

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Publication Date: 2024/05/14

Abstract: This project presents an innovative approach to stress detection by utilizing Convolutional Neural Networks (CNNs) to analyze emotional cues extracted from facial images. The proposed system employs CNNs, a class of deep learning models known for their efficacy in image recognition tasks, to automatically extract features from facial images. Through a combination of convolutional, pooling, and fully connected layers, the CNN learns hierarchical representations of facial expressions associated with various emotions, including those indicative of stress. The model is trained on a diverse dataset encompassing a wide range of facial expressions, allowing it to generalize well to unseen data. Transfer learning techniques may also be employed to leverage pre-trained CNN models, further enhancing performance with limited data.

Keywords: Facial Expressions Analysis, Emotional Recognition, Stress Level Indication.

DOI: https://doi.org/10.38124/ijisrt/IJISRT24APR2524

PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT24APR2524.pdf

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