Titlebook: Data Science and Network Engineering; Proceedings of ICDSN Suyel Namasudra,Munesh Chandra Trivedi,Pascal Lore Conference proceedings 2024 T

CLOWN

Bikram Sahoo,Seth Sims,Alexander Zelikovsky to obtain a good solution. In this paper, we would like to compare the results of both algorithms. Experimental results were examined with functions which were function maximization and results show that the Turbulent PSO outperform the GA.

perimenopause

ADAGE

Indict

Turbulent Particle Swarm Optimization and Genetic Algorithm for Function Maximization to obtain a good solution. In this paper, we would like to compare the results of both algorithms. Experimental results were examined with functions which were function maximization and results show that the Turbulent PSO outperform the GA.

yohimbine

Conference proceedings 2024), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering..

俗艷

Arnab Das,Bipa Datta,Moumita Mukherjee shown in the plots. The metrics and the running times are reported. There is not necessarily a certain training algorithm to be preferred, although there are some advantages and disadvantages for each. The code is available at ..

attenuate

Lecture Notes in Computer Sciencewell-known statistical measures and machine learning (ML) models. In this proposed system, we compare Linear Support Vector Classifier (LSVC), Logistic Regression (LR), Multinomial Na?ve Bayes (MNB), Random Forest Classifier (RFC), and Decision Tree Classifier (DTC) algorithms in which LR outperforms the other algorithms.

Baffle

Bikram Sahoo,Seth Sims,Alexander Zelikovskyadvances AI-powered computer vision systems by providing significant insights into the implementation of OpenCV with Python. The focus of future work will be on improving system accuracy and broadening its functional range.

朝圣者

https://doi.org/10.1007/978-1-4613-8342-0activity at ATMs. Therefore, in this work, abnormal behavior is observed using CNN and RNN in surveillance videos. These algorithms can be used to recognize faces, detect and track camera movements, and detect and identify the action required to prevent such activity.

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