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Titlebook: Hidden Markov Models and Applications; Nizar Bouguila,Wentao Fan,Manar Amayri Book 2022 The Editor(s) (if applicable) and The Author(s), u

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發(fā)表于 2025-3-21 19:14:09 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Hidden Markov Models and Applications
編輯Nizar Bouguila,Wentao Fan,Manar Amayri
視頻videohttp://file.papertrans.cn/427/426110/426110.mp4
概述Includes new advances on finite and infinite Hidden Markov Models (HMMs) and their applications from different disciplines.Tackles recent challenges related to the deployment of HMMs in real-life appl
叢書名稱Unsupervised and Semi-Supervised Learning
圖書封面Titlebook: Hidden Markov Models and Applications;  Nizar Bouguila,Wentao Fan,Manar Amayri Book 2022 The Editor(s) (if applicable) and The Author(s), u
描述This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs). In particular, the book presents recent inference frameworks and applications that consider HMMs. The authors discuss challenging problems that exist when considering HMMs for a specific task or application, such as estimation or selection, etc. The goal of this volume is to summarize the recent advances and modern approaches related to these problems. The book also reports advances on classic but difficult problems in HMMs such as inference and feature selection and describes real-world applications of HMMs from several domains. The book pertains to researchers and graduate students, who will gain a clear view of recent developments related to HMMs and their applications..
出版日期Book 2022
關(guān)鍵詞Hidden Markov models; machine learning, inference; Bayesian learning; infinite models; nonparametric Bay
版次1
doihttps://doi.org/10.1007/978-3-030-99142-5
isbn_softcover978-3-030-99144-9
isbn_ebook978-3-030-99142-5Series ISSN 2522-848X Series E-ISSN 2522-8498
issn_series 2522-848X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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發(fā)表于 2025-3-21 22:32:52 | 只看該作者
Online Learning of Inverted Beta-Liouville HMMs for Anomaly Detection in Crowd Scenes, This algorithm allows the update of parameter estimates after several increments of observation are processed (online). We also give positive vectors a special focus by using Inverted Beta-Liouville (IBL) mixtures as emission probabilities for our HMM. Using this distribution is expected to improve
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發(fā)表于 2025-3-22 14:46:00 | 只看該作者
Ravi Teja Vemuri,Muhammad Azam,Zachary Patterson,Nizar Bouguilasingle-stranded RNA virus, belonging to the family ., that majorly affects the lower respiratory tract of infants, the elderly, and immunocompromised people..Plants have played a vital role in therapeutic effects against many ailments since the dawn of human civilization on this planet. Several of t
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發(fā)表于 2025-3-22 17:30:55 | 只看該作者
Narges Manouchehri,Oumayma Dalhoumi,Manar Amayri,Nizar Bouguilacontinuing decline in formal political engagement (evidenced in falls in voting turnout, party membership and esteem of political representatives), but also in a context of a decade of internationally coordinated anti-globalization activism. It also coincided with the continued and accelerating deve
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發(fā)表于 2025-3-22 22:16:37 | 只看該作者
Wenjuan Hou,Wentao Fan,Manar Amayri,Nizar Bouguilaign: Mobilising support in parliament and among the medical profession, and taking action against anti-vivisectionists. Their successes included blocking the Dogs Protection Bill and arranging for the charitable status of anti-vivisection to be revoked.
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Bayesian Inference of Hidden Markov Models Using Dirichlet Mixtures,to HMM to improve its modeling capability. We conduct experiments with our model on real-world applications using video and speech data to display its effectiveness compared to other benchmark models.
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