Existing deep learning methods for facial emotion recognition only focus on optimizing network structures, utilizing fixed receptive fields for different images, and relying on feature extraction based on a single scale of receptive fields. However, this approach fails to fully capture the most critical facial regions. To address this limitation, this paper presents a novel technique for facial emotion recognition that employs a selective kernel network. The proposed method introduces a dedicated module called the selective kernel network, which is trained using transfer learning. This module ...
