Fast vehicle detection using augmented dataset based on RetinaNet

摘要

#$%^&*AU2019101133A420191031.pdf#####Abstract This invention lies in the field of computer vision and artificial intelligence. It is an vehicle video detection system of various kinds of images, especially cars, based on retina net. The invention consists of the following steps: Initially, we employ datasets to train convolutional networks . Then, we add the training set of data into the convolutional neural network in batches incessantly and continually adjust the parameters of the network such as base learning rate, weight, padding, stride or input and utilize back propagation, making the model approach the optimal performance. Finally, the test set of data is put into the trained neural network and different kinds of objects are recognized with % accuracy. 1Picture Acquisition (VOC dataset) Initialize the neural network Model training based on resnet and mobilenet Adjust parameters to train the network Yes No Reach the requiremen Prediction of the testing set Figure 3 3