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Titlebook: Evolution in Computational Intelligence; Proceedings of the 1 Vikrant Bhateja,Xin-She Yang,Carlos M. Travieso-Go Conference proceedings 202

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Zygfryd A. Nowak,Michal J. Cichysystems or the link to malicious website to steal confidential data such as hacking bank accounts, passwords leading to reduction in efficiency, security threats, consume server storage space, and unessential consumption of network bandwidth. Currently, there are 47.3% spam emails out of all emails
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Environmental Performance Measurementined ResNet50 model, which is a convolutional neural network (CNN) technique, are all machine learning classifiers. However, few research have examined the performances of these classifiers with different training sample sizes for the same remote sensing photos, with a particular focus on Sentinel-2
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2190-3018 volutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols, and architectures. This book is a valuable resource for postgraduate students in various engineering disciplines..978-981-99-6704-9978-981-99-6702-5Series ISSN 2190-3018 Series E-ISSN 2190-3026
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Automatic COVID Protocols-Based Human Entry Check System,he system detects the face and temperature of a human and sprays sanitizer, if the individual is taking each precaution the door which is related to the gadget will open and let the character move and if either of the precautions had been now not observed the door will no longer open and the photo o
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,Smart Hospitality: Understanding the ‘Green’ Challenges of Hotels and How IoT-Based Sustainable Devll buy-in from both their staff and customers. The authors of the paper fully advocate that the IoT technology implemented needs to effectively enable the hotel staff and customers with the ability and desire to adopt and cope with the act of ‘greening’/new ‘green’ practice. This paper discusses a s
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A Novel Knowledge Distillation Technique for Colonoscopy and Medical Image Segmentation, (IoU, Jaccard Index), and dice coefficient (.1 Score). Overfitting is one of the main issues with this methodology, which we were able to minimize through depth-wise model pruning and hyperparameter tuning. Finally, we achieved the Xception-Efficientb0 pair as knowledge distillation which can outpe
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Ensemble Machine Learning-Based Network Intrusion Detection System,ction system with Random Forest, AdaBoost, and LGBM ensemble models combined with a soft voting scheme as an improvement to currently employed models. The proposed model achieves an accuracy of 99.9% and a low false positive rate of 0.14 on the NSL-KDD benchmark dataset, with similar results on UNSW
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