基于深度学习的交通拥堵检测

Aimed at traffic congestion detection, a method of detecting traffic congestion images using convolutional neural network (CNN) was proposed. First, a neural network classification model with three layers of convolutional layers was designed based on the TensorFlow framework. Then, the classification model was trained and evaluated using road congestion and non-congestion pictures. Finally, the well-trained model was used to carry out road congestion detection. Compared with many other deep learning classification models, the proposed convolutional neural network model showed high efficiency in congestion detection, and the detection accuracy reached 98.1%.