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Lightweight models for fruits recognition

Image classification is a well known example of a complex problem that can be tackled using deep learning. In the latest period, convolutional neural networks were successfully applied in order to solve the problem. Moreover, recently, the research directions have been focusing more on developing lightweight models that can still achieve good classification performance. In this paper we propose a lightweight solution for solving an image classification problem. The solution is tested on an open dataset for fruits recognition. We achieve state of the art performance in terms of both classification accuracy and execution speed.