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Titlebook: Proceedings of Fifth Doctoral Symposium on Computational Intelligence; DoSCI 2024, Volume 3 Abhishek Swaroop,Vineet Kansal,Aboul Ella Hassa

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樓主: 會議記錄
21#
發(fā)表于 2025-3-25 05:55:12 | 只看該作者
,Toxicity Detection and?Classification in?Arabic Text,It achieved high .1-scores, indicating that it is effective in spite of all challenges presented by the corpus. From this study we conclude that natural language processing has proven its efficacy in identifying toxic Arabic language content. Furthermore, it paves the way to develop systems that detoxify Arabic text.
22#
發(fā)表于 2025-3-25 10:53:49 | 只看該作者
23#
發(fā)表于 2025-3-25 12:42:12 | 只看該作者
24#
發(fā)表于 2025-3-25 17:56:24 | 只看該作者
A Critical Assessment of Task Scheduling Algorithms in Cloud Computing: A Comparative Approach,e, the CloudSim 3.0.3 toolbox is used to simulate these methods under varying workload conditions. Additionally, a collection of metrics is computed, and these measures are used to compare and evaluate the aforementioned algorithms.
25#
發(fā)表于 2025-3-25 21:51:09 | 只看該作者
EnviroWatch: A Comprehensive Environmental Monitoring Web Frame and Cleanup Coordination System Using CNN,er to identify and classify garbage. Government bodies and NGOs can access the platform to gather crucial data and coordinate cleanup initiatives, fostering a collaborative effort toward environmental well-being.
26#
發(fā)表于 2025-3-26 02:55:16 | 只看該作者
27#
發(fā)表于 2025-3-26 06:06:32 | 只看該作者
Enhancing Suspect Identification: Automated Composite Sketch Generation and Recognition,ques use computer vision algorithms—deep learning models to accurately capture facial features and compare them to a database of known faces. This review examines the latest techniques for creating and recognizing facial images, investigating their applications, challenges, and potential future developments.
28#
發(fā)表于 2025-3-26 09:33:35 | 只看該作者
29#
發(fā)表于 2025-3-26 13:36:22 | 只看該作者
30#
發(fā)表于 2025-3-26 19:16:05 | 只看該作者
,Machine Learning-Based Comprehensive Framework for?Stock Prediction,in market size forecasting. Through preprocessing and feature extraction, the LSTM model captures a series of economic time series. This study focuses on hyperparameter optimization and external parameters, which significantly improve the accuracy of the model.
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