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Titlebook: Congress on Intelligent Systems; Proceedings of CIS 2 Mukesh Saraswat,Harish Sharma,Jagdish Chand Bansal Conference proceedings 2022 The Ed

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11#
發(fā)表于 2025-3-23 10:43:13 | 只看該作者
Analyzing a Raga-Based Bollywood Song: A Statistical Approach,al (IOI) graph, study of note duration, etc. Furthermore, the variation in melody and rhythm throughout the song at different intervals would be investigated using the statistical parameterization approach with the help of Andrews plot. The song used by us for our analysis is . from the movie . (200
12#
發(fā)表于 2025-3-23 15:24:16 | 只看該作者
Security Prioritized Heterogeneous Earliest Finish Time Workflow Allocation Algorithm for Cloud Comy requirements and, therefore, assigned on the more reliable virtual machines. In experimental evaluation, SPHEFT is compared with the standard HEFT algorithm for varying set of tasks. The experimental results show that SPHEFT has better performance on security overhead and more excellent efficienci
13#
發(fā)表于 2025-3-23 21:35:05 | 只看該作者
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發(fā)表于 2025-3-24 00:33:52 | 只看該作者
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發(fā)表于 2025-3-24 04:22:41 | 只看該作者
Conference proceedings 2022 neural network, image/video classification, soft computing for machine vision, pattern recognition,human–computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural networ
16#
發(fā)表于 2025-3-24 08:41:43 | 只看該作者
2367-4512 cognition,human–computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural networ978-981-16-9415-8978-981-16-9416-5Series ISSN 2367-4512 Series E-ISSN 2367-4520
17#
發(fā)表于 2025-3-24 11:02:59 | 只看該作者
18#
發(fā)表于 2025-3-24 18:10:49 | 只看該作者
,Reaction—Advection—Dispersion Equation,e. The mobile application also provides necessary remedies for the identified disease with the help of hyperlink available in mobile application. The achieved probability that the model can truly classify the input image in this project was 97.67%, and the obtained validation accuracy was 98.86%. A
19#
發(fā)表于 2025-3-24 21:30:37 | 只看該作者
20#
發(fā)表于 2025-3-24 23:47:47 | 只看該作者
Sanjivi Sundar,Akshima T. Ghate an ensemble of long short-term memory (LSTM) model. It analyzes the results of individual LSTM models in predicting stock prices and creates an ensemble model in an effort to improve the overall performance of the prediction. The proposed model is evaluated on real-world data of 4 companies from Ya
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