Research and application of talent training evaluation model based on deep learning

Abstract

The application of deep learning technology in target detection algorithm significantly improves the performance of the algorithm. Based on the traditional target detection algorithm, the task of target detection is summarized, including evaluation index, open data set, algorithm framework and the defects of traditional algorithm. Therefore, taking the needs of object detection as the fulcrum, the training goal of research travel talents is clarified in this paper. There are two classification criteria: whether there is an explicit regional suggestion and whether a prior anchor frame is defined. The existing target detection algorithms are classified, and the evolutionary route of each algorithm is reviewed, and the mechanism, advantages, limitations and application scenarios of each method are summarized. The performance of representative target detection algorithms in open data sets is compared and analyzed.