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Titlebook: Inventive Systems and Control; Proceedings of ICISC V. Suma,Zubair Baig,Pascal Lorenz Conference proceedings 2022 The Editor(s) (if applica

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發(fā)表于 2025-3-28 18:03:07 | 只看該作者
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發(fā)表于 2025-3-29 01:11:59 | 只看該作者
A Decentralised Blockchain-Based Secure Authentication Scheme for IoT Devices,schemes to adversarial threats. We present a blockchain-based decentralised authentication scheme for peer-to-peer IoT networks. The scheme is designed to foster secure authentication for IoT devices in an integrated IoT-cloud network topology.
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發(fā)表于 2025-3-29 06:33:06 | 只看該作者
Anti-cancer Drug Response Prediction System Using Stacked Ensemble Approach,. In this ensemble algorithm, random forest, linear regression, and Gaussian Na?ve Bayes are stacked and enhanced with the voting average method. The efficiency level obtained in this research is 97.5%. The dataset is taken from GDSC and GCLE for the experimentation.
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發(fā)表于 2025-3-29 08:40:25 | 只看該作者
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Brain MR Image Segmentation for Tumor Identification Using Hybrid of FCM Clustering and ResNet,50 model. A dataset provided by Kaggle comprising brain MR images has been used in training and testing the model. The image segmentation results are compared with the K-means clustering method using various performance metrics. The maximum accuracy of 91.18% has been observed at 350 epochs by the proposed method.
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發(fā)表于 2025-3-29 17:56:55 | 只看該作者
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2367-3370 a reference resource for researchers and practitioners in aThis book presents selected papers from the 6th International Conference on Inventive Systems and Control (ICISC 2022), held on 6–7 January 2022 at JCT College of Engineering and Technology, Coimbatore, India. The conference proceedings of
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發(fā)表于 2025-3-30 01:37:09 | 只看該作者
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發(fā)表于 2025-3-30 07:54:53 | 只看該作者
Convolutional Neural Networks as a Quality Control in 4.0 Industry for Screws and Nuts, pattern-based techniques present severe problems for achieving efficient algorithms with high success and are usually strongly influenced by environmental factors such as illumination, dust and movement. Convolutional neural networks are particularly effective as image classifiers, but it is a fiel
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