Research Based on the Application of Computer Software Technology in the Era of Big Data
In the context of the current big data era,the rapid development of computer software technology has led mankind into a new era of information explosion.In the traffic target recognition problem,computer software technology is also widely used.However,the low-light traffic environ-ment will significantly reduce the quality of the image,which in turn affects the accuracy of recognition.In order to solve this problem,the study proposes an improved algorithm CLAHE-GhostNet-CBAM-Yolov4(CGC-Yolov4)for Yolov4.The study uses the CLAHE image enhancement algorithm for the input image in the input module,replaces the Yolov4 backbone network with GhostNet,and adds the attention mechanism at the end of the bottleneck network.The results of the performance tests show that in pedestrian target recognition,the F1 score of the proposed model reaches 91%up to 98%in the 12th iteration.The experimental results show that compared to the traditional model CGC-Yolov4 not only improves the recognition efficiency,but also maintains excellent real-time processing capability,which proves its practicality and effectiveness in night-time traffic target recognition appli-cations.