CONFERENCE / ICCAIS-2026

Facial expression analysis are one of the primary methods of identifying emotions which scans as very interesting in its combination with the elements of psychology and technology. Facial emotion recognition Face recognition has been given a significant boost with the application of deep learning algorithms with the capacity to identify common emotions. A lot of progress has been achieved in the automatic facial emotion recognition (FER) in recent years. The technology has found use in many industries to enhance human machine interaction particularly in human-centred computing and the nascent emotional artificial intelligence (EAI) field. The research objective of researchers is to improve the functionality of systems in the process of identifying and discerning human facial expression and behavior in diverse scenarios. The contribution of the RCNN to the area has been intense due to the ample formation of these networks which led to the generation of different architectures as part and parcel of the endeavor to encounter increasingly complicated problems. This paper investigates the present progress of automated emotion recognition AER technology which uses computational intelligence methods for its development. The research presents field development through its examination of contemporary deep learning models which improved emotion detection results across various data types and real-world situations. It provides the summary of the most recent progress of the RCNN architecture of FER in the past decade, illustrating the mechanisms of collaboration of deep learning based methods and special databases to give the strongest results.