Method for detecting PCB electronic component based on ERFAM-YOLOV3 network structure
A technology of electronic components and network structure, applied in the direction of biological neural network model, neural architecture, computer components, etc., can solve the problems of large number of detection network parameters, low detection efficiency, slow operation speed, etc. The effect of fast speed and few parameters
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[0051] A kind of detection method that the present invention provides based on the PCB electronic component of ERFAM-YOLOV3 network structure, is characterized in that, comprises the following concrete steps:
[0052] S1, there are 1,000 images, 29 instrument categories and 182,900 electronic components in the PCB electronic component dataset. The PCB electronic component dataset is divided into 8:2, that is, 8 pieces of data are randomly selected for training, and 2 pieces of data are used for detection. data.
[0053] S2, the ERFAM-YOLOV3 network is designed using the modular design strategy and the matching algorithm between the anchor size and the effective receptive field size. Further specific steps related to S2 are as follows:
[0054] S201, first load the YOLOV3 model, each convolution layer has two parameters: weight and bias. We will set the weights of each layer to random values and the bias to 0. The BN layer has four parameters - weight, bias, running mean a...
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