Object detection is to accurately identify and locate the target in the image. With the development of deep learning, object detection algorithm has achieved very high achievements, for example, object detection algorithm is applied to security, medical, transportation, military, automatic driving and so on. This paper reviews the progress of target detection algorithms by consulting many literatures at home and abroad. Firstly, the research status of object detection is introduced, and the dataset, evaluation index and convolutional neural network used in the process of target detection are provided. Secondly, it compares some mainstream object detection algorithms at this stage. The starting point of this paper is to help others quickly understand the target detection algorithm. Readers can find the appropriate object detection algorithm according to their own project and improve it on this basis. Finally, combined with the current research hotspots, the future development trend is analyzed.
A Survey of Deep Learning Object Detection Algorithm
2022-10-12
1280465 byte
Conference paper
Electronic Resource
English
Deep learning for crack-like object detection
TIBKAT | 2023
|A survey of deep learning methods and software tools for image classification and object detection
British Library Online Contents | 2016
|Deep Learning in Lane Marking Detection: A Survey
IEEE | 2022
|Deep Learning Based Object Detection on Gas Cylinders
Springer Verlag | 2024
|