A Convolution Neural Network Based Classification Approach for Recognizing Traditional Foods of Bangladesh from Food Images

摘要

The process of identifying food items from an image is one of the promising applications of visual object recognition in computer vision. However, analysis of food items is a particularly challenging task due to the nature of their has achieved by traditional approaches in the field. Deep neural networks have exceeded such solutions. With a goal to successfully applying computer images, which is why a low classification accuracy vision techniques to classify food images based on Inception-v3 model of TensorFlow platform, we use the transfer learning technology to retrain the food category datasets. Our approach shows auspicious results with an average accuracy of 95.2% approximately in correctly recognizing among 7 traditional Bangladeshi foods.