Jul 12, 2021 · Our method is competitive and outperforms current state-of-the-art techniques and achieves a classification accuracy of 92.85\% and an f1 score ...
Sep 7, 2024 · Current approaches for stress classification use traditional machine learning algorithms trained on features computed from multiple sensor ...
Jul 12, 2021 · Current approaches for affective state classification use traditional machine learn- ing algorithms with features computed from multiple sensor.
This work proposes a novel Convolutional Neural Network based stress detection and classification framework without any feature computation using data from ...
Stress Classification and Personalization: Getting the most out of the least. Ramesh Kumar Sah, Hassan Ghasemzadeh. July 2021.
Automated stress detection using physiological sensors is challenging due to inaccurate labeling and individual bias in the sensor data.
Co-authors ; Stress classification and personalization: Getting the most out of the least. RK Sah, H Ghasemzadeh. arXiv preprint arXiv:2107.05666, 2021. 12, 2021.
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May 10, 2024 · We aim to study the differences between personalized and generalized machine learning models for 3-class emotion classification (neutral, stress, and amusement ...
Stress detection and monitoring is an active area of research with important implications for the personal, professional, and social health of an individual ...
May 10, 2024 · We aim to study the differences between personalized and generalized machine learning models for 3-class emotion classification (neutral, stress ...