AffectNet Dataset

AffectNet is a large-scale facial expression recognition (FER) dataset used extensively to benchmark and improve automated emotion detection systems. Current research focuses on enhancing model accuracy and robustness using techniques like convolutional neural networks (CNNs), modified VGG16 architectures, and attention mechanisms to address challenges posed by diverse facial expressions and real-world image variations. The dataset's significance lies in its contribution to advancing FER technology, with implications for applications ranging from human-computer interaction to mental health monitoring, while also highlighting issues of dataset bias and privacy in AI development.