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Titlebook: Computational Science – ICCS 2022; 22nd International C Derek Groen,Clélia de Mulatier,Peter M. A. Sloot Conference proceedings 2022 The Ed

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發(fā)表于 2025-3-21 20:06:18 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Computational Science – ICCS 2022
副標(biāo)題22nd International C
編輯Derek Groen,Clélia de Mulatier,Peter M. A. Sloot
視頻videohttp://file.papertrans.cn/234/233097/233097.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Science – ICCS 2022; 22nd International C Derek Groen,Clélia de Mulatier,Peter M. A. Sloot Conference proceedings 2022 The Ed
描述.The four-volume set LNCS 13350, 13351, 13352, and 13353 constitutes the proceedings of the 22ndt International Conference on Computational Science, ICCS 2022, held in London, UK, in June 2022.*..The total of 175 full papers and 78 short papers presented in this book set were carefully reviewed and selected from 474 submissions. 169 full and 36 short papers were accepted to the main track; 120 full and 42 short papers were accepted to the workshops/ thematic tracks. ..*The conference was held in a hybrid format.
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; classification methods; computer networks; computer systems; computer vision; co
版次1
doihttps://doi.org/10.1007/978-3-031-08754-7
isbn_softcover978-3-031-08753-0
isbn_ebook978-3-031-08754-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

書目名稱Computational Science – ICCS 2022影響因子(影響力)




書目名稱Computational Science – ICCS 2022影響因子(影響力)學(xué)科排名




書目名稱Computational Science – ICCS 2022網(wǎng)絡(luò)公開度




書目名稱Computational Science – ICCS 2022網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Science – ICCS 2022被引頻次




書目名稱Computational Science – ICCS 2022被引頻次學(xué)科排名




書目名稱Computational Science – ICCS 2022年度引用




書目名稱Computational Science – ICCS 2022年度引用學(xué)科排名




書目名稱Computational Science – ICCS 2022讀者反饋




書目名稱Computational Science – ICCS 2022讀者反饋學(xué)科排名




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Compiling Linear Algebra Expressions into?Efficient Codeated into efficient code, since optimized linear algebra libraries and frameworks require expressions in index-free form. To address this problem, we developed ., a tool that automatically converts linear algebra expressions with indices into index-free linear algebra expressions that we map efficie
板凳
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地板
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Devulgarization of?Polish Texts Using Pre-trained Language Modelseaning of the text. We fine-tune three pre-trained language models on a newly created parallel corpus of vulgar/non-vulgar sentence pairs, then we evaluate style transfer accuracy, content preservation and language quality. To the best of our knowledge, the proposed solution is the first of its kind
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發(fā)表于 2025-3-22 09:35:40 | 只看該作者
Data-Driven Discovery of?Time Fractional Differential Equationshat is, learning differential equations/fractional differential equations via data. In [.], Schaeffer proposed a machine learning algorithm to learn the differential equation via data discovery. We extend Schaeffer’s work in the case of time fractional differential equations and propose an algorithm
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發(fā)表于 2025-3-22 13:22:10 | 只看該作者
Wide Ensembles of?Neural Networks in?Music Genre Classificationjob manually. That is why there is a need to create robust and efficient methods that automatically help to do this task. In this paper, music genre recognition is implemented by exploiting the potential of wide ensembles of neural network classifiers. Creating infrequently used types of ensembles i
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發(fā)表于 2025-3-22 19:20:59 | 只看該作者
Particle Swarm Optimization Configures the?Route Minimization Algorithmristics to tackle this task, they are often heavily parameterized, and improperly tuned hyper-parameters adversely affect their performance. We exploit particle swarm optimization to select the pivotal hyper-parameters of a route minimization algorithm applied to the pickup and delivery problem with
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發(fā)表于 2025-3-22 22:11:51 | 只看該作者
Practical Aspects of?Zero-Shot Learning. However, since none of them seems to be an “overall winner”, development of a meta-classifier(s) combining “best aspects” of individual classifiers can be attempted. In this context, state-of-the-art zero-shot learning methods are compared for standard benchmark datasets. Next, multiple meta-class
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Analyzing the?Usefulness of?Public Web Camera Video Sequences for?Calibrating and?Validating Pedestrternative to using data obtained in such a way is using data from public web cameras. The article presents a case study of using public web cameras in the analysis of pedestrian dynamics and social behavior. We have applied YOLOv3 object detector trained on the COCO dataset in order to identify obje
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