residual networks (ResNet)

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• Published Subscription Original Research 28 Apr 2025

  Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks

  By V. Anusuya, S. Sakkaravarthi, M. Rethinakumari, Sridhar S.

  Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …

  Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article →