Download PDFOpen PDF in browserResearch on Fine-Grain Model Recognition Based on Branch Feedback Convolution Neural NetworkEasyChair Preprint 8425 pages•Date: March 19, 2019AbstractFine-grained vehicle identification has a wide range of applications in many fields, and the requirements for recognition accuracy are high in various application scenarios. In this paper, a branch fusion convolutional neural network algorithm for fine-grained car recognition is designed. The VGG16 convolutional neural network is merged with AlexNet to form a bifurcated fusion convolutional neural network. On this basis, the multi-branch training idea of GoogleNet is cited to make the network model stabilize and converge during training. The network was trained and tested on the CompCars fine-grained car dataset. The correct rate of the test set Top-1 reached 91.29%, and the model was accurate and effective. Keyphrases: Feedback convolutional neural network, VGG16, multi-branch training
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