#5818. Quantitative performance evaluation of object detectors in hazy environments

July 2026publication date
Proposal available till 15-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Signal Processing;
Software;
Computer Vision and Pattern Recognition;
Artificial Intelligence;
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Abstract:
We present a quantitative performance analysis of a wide range of state-of-the-art object detection models, such as Mask R-CNN He et al.(20XX)[8], RetinaNet Lin et al.(20XX)[17] and EfficinetDet Tan et al.(20XX)[28] in haze affected environments. This work uses two key performance metrics (Mean Average Precision and Localised Recall Precision) to provide a nuanced view of real world performance of these models in an on-road driving application.
Keywords:
Deep learning; Haze; Object detection

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