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- W4368233064 abstract "Detection of road objects is crucial for autonomous vehicles, and it needs constant improvement. There are certain challenges in this area of computer vision such as extreme weather conditions, blurred images. These challenges limit the object detection performance. In this paper, we analyze and enhance the approach called CenterNet, which is an anchor-free detector. Dataset used in this paper comprises of real-time data, which is grouped in different ways to accommodate the range of real-world scenarios. The experimental results indicate that the suggested method can greatly increase object identification performance in a variety of traffic situations." @default.
- W4368233064 created "2023-05-05" @default.
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- W4368233064 date "2023-01-01" @default.
- W4368233064 modified "2023-09-25" @default.
- W4368233064 title "Vehicle Object Detection Using Deep Learning-Based Anchor-Free Detector" @default.
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- W4368233064 doi "https://doi.org/10.1007/978-981-19-7455-7_34" @default.
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