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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Improving Chairlift Security with Deep Learning
verfasst von : Kevin Bascol, Rémi Emonet, Elisa Fromont, Raluca Debusschere
Erschienen in: Advances in Intelligent Data Analysis XVI
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Abstract
This paper shows how state-of-the-art deep learning methods can be combined to successfully tackle a new classification task related to chairlift security using visual information. In particular, we show that with an effective architecture and some domain adaptation components, we can learn an end-to-end model that could be deployed in ski resorts to improve the security of chairlift passengers. Our experiments show that our method gives better results than already deployed hand-tuned systems when using all the available data and very promising results on new unseen chairlifts.