2021
DOI: 10.20944/preprints202106.0590.v1
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Survey and Performance Analysis of Object Detection in Challenging Environments

Abstract: Recent progress in deep learning has led to accurate and efficient generic object detection networks. Training of highly reliable models depends on large datasets with highly textured and rich images. However, in real-world scenarios, the performance of the generic object detection system decreases when (i) occlusions hide the objects, (ii) objects are present in low-light images, or (iii) they are merged with background information. In this paper, we refer to all these situations as challenging environments. … Show more

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Cited by 17 publications
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References 85 publications
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