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Titlebook: KI 2021: Advances in Artificial Intelligence; 44th German Conferen Stefan Edelkamp,Ralf M?ller,Elmar Rueckert Conference proceedings 2021 S

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發(fā)表于 2025-3-21 20:09:38 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱KI 2021: Advances in Artificial Intelligence
副標(biāo)題44th German Conferen
編輯Stefan Edelkamp,Ralf M?ller,Elmar Rueckert
視頻videohttp://file.papertrans.cn/542/541650/541650.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: KI 2021: Advances in Artificial Intelligence; 44th German Conferen Stefan Edelkamp,Ralf M?ller,Elmar Rueckert Conference proceedings 2021 S
描述This book constitutes the refereed proceedings of the 44.th. German Conference on Artificial Intelligence, KI 2021, held in September/October 2021. Due to COVID-19 pandemic the conference was held virtually.. The 16 full and 4 short papers with one extended abstract were carefully reviewed and selected from 59 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; computer networks; computer science; computer systems; computer vision; data min
版次1
doihttps://doi.org/10.1007/978-3-030-87626-5
isbn_softcover978-3-030-87625-8
isbn_ebook978-3-030-87626-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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0302-9743 r 2021. Due to COVID-19 pandemic the conference was held virtually.. The 16 full and 4 short papers with one extended abstract were carefully reviewed and selected from 59 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all meth
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發(fā)表于 2025-3-22 03:18:32 | 只看該作者
RP-DQN: An Application of Q-Learning to Vehicle Routing ProblemsProblem (CVRP). Additionally, we are the first to tackle the Multiple Depot Vehicle Routing Problem (MDVRP) with Reinforcement Learning (RL) and demonstrate that this problem type greatly benefits from our approach over other Machine Learning (ML) methods.
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An Agent Architecture for Knowledge Discovery and Evolutionm incoming observations. It then uses rules to analyse the current situation and a Bayesian network for finding plausible explanations for unexpected situations. The architecture is evaluated and analysed on a use case application for monitoring daily household electricity consumption patterns.
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Crop It, but Not Too Much: The Effects of Masking on the Classification of Melanoma Imageshat cropping increases classification performances, but specificity decreases when cropping is applied together with masking out healthy skin regions. An analysis of Grad-CAM saliency maps shows that in fact our CNN models have the tendency to focus on healthy skin at the border when a nevus is classified.
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