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- W4320730006 abstract "Object recognition is a basic and difficult task in computer vision. Its purpose is to identify the object and give its exact position in the picture. In recent years, it has attracted extensive attention and gradually become a research hotspot. With the continuous development of object detection, some investigators have been solving existing problems and started to apply deep neural networks to the task. Despite the great progress in the research work surrounding the mission, there are few reviews of the mission, lacking a comprehensive review of its development in recent years. Given this period of rapid development, I will give an overview of object detection and present what methods have been used in object detection in recent years to improve task performance. This paper's goal is to give an exhaustive overview of the most latest developments in the area brought about by deep learning technology. At the same time, the possible problems in the task are analyzed, and the potential problems in the task are analyzed." @default.
- W4320730006 created "2023-02-15" @default.
- W4320730006 creator A5035269751 @default.
- W4320730006 date "2023-02-10" @default.
- W4320730006 modified "2023-10-05" @default.
- W4320730006 title "Recent Deep Neural Networks for Object Detection" @default.
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- W4320730006 doi "https://doi.org/10.54097/hset.v31i.5153" @default.
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