面向上下文的双流情绪感知Swin变换器在学术情绪识别中的应用

Abstract Enhancing academic engagement and adaptive learning systems requires an understanding of students’ emotions in the classroom. Conventional facial expression recognition techniques frequently fall short in educational environments because of issues such inadequate lighting, occlusion, changing head positions, and the requirement to record contextual data outside of the face. With three significant innovations, this study suggests a unique framework for robust academic emotion recognition called Context Attentive Cascaded Preprocessing with Dual Stream Emotion Aware Swin Transformer (CA