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Titlebook: Intelligent Computing Theories and Application; 17th International C De-Shuang Huang,Kang-Hyun Jo,Prashan Premaratne Conference proceedings

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發(fā)表于 2025-3-21 16:56:50 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Intelligent Computing Theories and Application
副標(biāo)題17th International C
編輯De-Shuang Huang,Kang-Hyun Jo,Prashan Premaratne
視頻videohttp://file.papertrans.cn/470/469488/469488.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Intelligent Computing Theories and Application; 17th International C De-Shuang Huang,Kang-Hyun Jo,Prashan Premaratne Conference proceedings
描述This two-volume set of LNCS 12836 and LNCS 12837 constitutes - in conjunction with the volume LNAI 12838 - the refereed proceedings of the 17th International Conference on Intelligent Computing, ICIC 2021, held in Shenzhen, China in August 2021. The 192 full papers of the three proceedings volumes were carefully reviewed and selected from 458 submissions..?The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is “Advanced Intelligent Computing Methodologies and Applications.”.The papers are organized in the following subsections: Artificial Intelligence in Real World Applications, Biomedical Informatics Theory and Methods, Complex Diseases Informatics, Gene Regulation Modeling and Analysis, Intelligent Computing in Computational Biology, and Protein Structure and Function Prediction..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; computer networks; computer vision; data mining; deep learning; image analysis; i
版次1
doihttps://doi.org/10.1007/978-3-030-84532-2
isbn_softcover978-3-030-84531-5
isbn_ebook978-3-030-84532-2Series 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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Exploring Multi-scale Temporal and Spectral CSP Feature for Multi-class Motion Imagination Task Classsifier. We extend CSP feature extractor to multiscale temporal and spectral conditions. Experimental results show that compared with many improved CSP features and several deep learning methods of recent years, the multiscale temporal and spectral CSP features achieve superior classification accuracy.
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Conference proceedings 2021ational Conference on Intelligent Computing, ICIC 2021, held in Shenzhen, China in August 2021. The 192 full papers of the three proceedings volumes were carefully reviewed and selected from 458 submissions..?The ICIC theme unifies the picture of contemporary intelligent computing techniques as an i
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HOMC: A Hierarchical Clustering Algorithm Based on Optimal Low Rank Matrix Completion for Single Celustering based on correlation-based distance for grouping those imputed data points, and optimal number of clusters can be determined by integrating three classical measures. Experimental results have showed that HOMC is capable of distinguishing cellular differences and the clustering performance is superior to other state-of-the-art methods.
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mzMD: A New Storage and Retrieval System for Mass Spectrometry Dataalization applications to query for summaries (representative peak sets) of given data windows. We propose criteria to evaluate the quality of summaries of data windows. Experimental statistics on real LC–MS data sets verified the high speed of mzMD in retrieving high-quality summaries of data windows. The source code is freely available at ..
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Incorporating Knowledge Base for Deep Classification of Fetal Heart Ratean solve the problem of noise and imbalance in the data. To verify the effectiveness of our proposed framework, we conduct extensive experiments on a real-world dataset. The experimental results show that the performance of our framework is better than other methods.
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