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| With the rapid development of deep learning, more and more image recognition models are applied to daily life. For the current neural network model, the recognition accuracy of large model is higher and higher, but the more resources are needed. The lightweight of neural network model is more conducive to the application in life. In this paper, a THMobile model with smaller size and higher accuracy is proposed based on MobileNet. On the self-made garbage dataset, the classification accuracy of it reaches 91.2%, obtaining better performance than MobileNet. And it also performs better on CIFAR-10 than MobileNet. |
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| Keywords:image recognition, MobileNet, garbage classification, THMobile |
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