• Mahammad Mudassir
• Sowmya K
• Mohammed Rayyan Shaikh
• Muhammad Masood Sayiq
• Shahin Gazi

In the realm of artificial intelligence systems and human-computer interaction, understanding human emotions via facial cues has gained significant attention. This paper proposes a deep learning-based Facial Emotion Detection system capable of detecting emotions like joy, sorrow, anger, fear, disgust and surprise by identifying facial images. Automatic feature extraction is carried out using Convolutional Neural Networks (CNNs) within the system and classification. The model undergoes training with labelled datasets such as FER-2013 and CK+, with preprocessing methods such as grayscale normalization and facial landmark detection to improve performance. Applications range across healthcare, education, customer service, and security. This paper presents the architecture, methodology, datasets, and experimental results of the proposed emotion detection system, emphasizing its real-world applicability and accuracy

Facial Emotion Detection, Convolutional Neural Networks (CNNs), Deep Learning, Human-Computer Interaction (HCI), FER-2013 Dataset, Facial Landmark Detection, Real-Time Emotion Recognition, Affective Computing

"FACIAL EMOTION DETECTION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.106-109, July-2025, Available :http://www.jetir.org/papers/JETIRGX06019.pdf

"FACIAL EMOTION DETECTION USING DEEP LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp106-109, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06019.pdf