Review of Target Detection Algorithms Based on Deep Learning
Journal Title: Automotive Engineer - Year 2024, Vol 51, Issue 1
Abstract
This paper introduced the development of object detection datasets and the establishment of basic evaluationmetrics,and based on this,it reviewed different categories of object detection algorithms.Single-stage and two-stage detectionalgorithms,as well as corresponding optimization algorithms,were analyzed separately.Highlighting the iterative process ofdetection speed and accuracy,the paper elaborated the challenges and difficulties in object detection algorithms.A summaryand outlook for the improvement of the method itself and the optimization design under the application requirements of thealgorithm were proposed in the paper,which indicated training supervision of object detection,the difficulty of detecting smalltargets by the algorithm.At the same time,the paper also indicated the coordination between detection speed and accuracy inreal-time detection tasks and multimodal fusion application,as well as the important significance of the interpretability ofalgorithm operation for further improving the algorithm.
Authors and Affiliations
Zeng Wenbing, Li Jun
Keywords
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- EP ID EP731783
- DOI 10.20104/j.cnki.1674-6546.20230382
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