Recently, chronic patients are taking multiple medications incorrectly and taking the wrong medications due to similarity of drugs.It is possible that taking the improper medication can result in hazardous interactions with other medications or they will counteract the intended benefits of the medications, resulting in extra severe repercussions such as acute complications. The conventional methods are failed to provide the maximum efficiency. Therefore, this article is focused on implementation of faster recurrent convolutional neural networks (FR-CNN), which is capable of extracting the features from images. FR-CNN mainly used to analyze the patterns of the medicines and extracts the deep features. Further, classification of medicines is carried out by comparing with ground truth labels. The simulation results shows that the proposed system resulted in superior performance as compared to state of art approaches.