KLASIFIKASI EMOSI MENGGUNAKAN COMPUTER VISION DAN CONVOLUTIONAL NEURAL NETWORKS - Nurdiyansah , Andri; Rochmawati, Dwi Robiul (LPPM Politeknik Pajajaran ICB Bandung, 2025)
This research focuses on the development of an emotion classification system utilizing computer vision and Convolutional Neural Networks (CNN). This model was trained on the FER2013 dataset, which contains 35,809 facial images categorized into seven emotions. Metode seperti augmentasi data dan normalisasi piksel diterapkan untuk meningkatkan ketahanan model. The CNN architecture achieved an accuracy of 85%, demonstrating its effectiveness in recognizing emotions such as happiness and anger. This research highlights the potential integration of emotion-aware systems into applications such as human-computer interaction and personalized services, emphasizing technical innovation in AI-based solutions. Keywords: Emotion Classification; Computer Vision; CNN; FER2013; Deep Learning