RscaNet:a novel attention mechanism for image classification model

In computer vision technology, image classification task is an important technical progress. In view of the fact that the current garbage classification cannot effectively classify these different kinds of garbage, resulting in resource waste, environmental pollution and other problems, we propose to improve the deep learning model of ResNet to achieve classification. We added CBAM attention mechanism module and FocalLoss function to improve classification accuracy. We evaluate the performance of this model in different types of garbage classification data sets, and the results show that compared with other models, our model improved 0.16, 0.07, 0.06, 0.17 in fl-score, accuracy, percsion, and recall, respectively. Experimental results show that this method can effectively improve the image classification effect.