Fine-Grained Image Classification Based on Attention Mechanism and Fusion Method

Due to the evolution of computer vision, the recognition of fine-grained image classification problems is gaining more and more importance. This paper organizes an overview of the principal conceptualisations of the research and general approaches within the domain of fine-grained image classification, in the view of the mechanisms of attention, image fusion procedures, and a mixture of both. The attention mechanism-based approach primarily enhances the capability of the model in identifying small variations through the focus on the main regions of interest and discriminative characters. The research based on the combination of the attention mechanism with the fusion method further capitalizes on the strong merits of both approaches and thereby promotes better classification performance of the model in difficult scenes. This article aims to overview of the recent advances in associated research methodology and to assist scientists in being more attentive to the progress of research and related current information.