Research on Garbage Image Classification Based on TensorFlow
This paper explores how to use TensorFlow to classify garbage images.Using Convolutional Neural Networks(CNN)as the main method,accurate classification of different types of garbage images is achieved through training and fine-tuning on large datasets.The research results indicate that the proposed model performs excellently on the test set,with an overall classification accuracy of over 90%.In addition,through visual analysis of the model,its learning method for image features is revealed,further deepening the understanding of the classification process.In summary,deep learning methods based on TensorFlow have broad application prospects in the field of garbage image classification.
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