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• W2086921491 abstract "We present a fast Bayesian algorithm for category-level object detection in natural images. We modify the popular Naive Bayes Nearest Neighbour classification algorithm to make it suitable for evaluating multiple sub-regions in an image, and offer a fast, filtering-based alternative to the multi-scale sliding window approach. Our algorithm is example-based and requires no learning. Tests on standard datasets and robotic scenarios show competitive detection rates and real-time performance of our algorithm." @default.
• W2086921491 created "2016-06-24" @default.
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• W2086921491 date "2014-10-01" @default.
• W2086921491 modified "2023-09-25" @default.
• W2086921491 title "An efficient Naive Bayes approach to category-level object detection" @default.
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• W2086921491 doi "https://doi.org/10.1109/icip.2014.7025332" @default.
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