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Titlebook: Intelligent Systems for Smart Cities; Select Proceedings o Anand J. Kulkarni,Naoufel Cheikhrouhou Conference proceedings 2024 The Editor(s)

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41#
發(fā)表于 2025-3-28 18:28:43 | 只看該作者
42#
發(fā)表于 2025-3-28 20:29:11 | 只看該作者
Anand J. Kulkarni,Naoufel CheikhrouhouComprises peer-reviewed proceedings of the conference ICISA 2023.Covers the latest research in technological advances in the field of artificial intelligence and machine learning.Enriches understandin
43#
發(fā)表于 2025-3-29 02:33:11 | 只看該作者
44#
發(fā)表于 2025-3-29 04:29:24 | 只看該作者
https://doi.org/10.1007/978-981-99-6984-5Smart Cities; Banking and Finance; Social-Media, Cyber security & Crime Prevention; Infrastructure; Heal
45#
發(fā)表于 2025-3-29 09:06:11 | 只看該作者
Manifesta: An Event Management Platform Using Recommendation System way by using an online platform. A new event-driven platform for smart cities is proposed in this paper for simplifying event management services. This paper proposes an intelligent website named “Manifesta” for event management services that would enable an intelligent environment for event manage
46#
發(fā)表于 2025-3-29 13:40:39 | 只看該作者
An Empirical Study on the Information Security Threats Due to Remote Working Environmentsurity issues. Insecure human internet use habits (unprotected home networks, unpatched software), organizational policies regarding cyber security during remote work, insecure teleconferencing and video conferencing practices and sophisticated cyber-attack techniques are a few of the reasons respons
47#
發(fā)表于 2025-3-29 17:29:51 | 只看該作者
Intelligent Surveillance Tower for Detection of the Drone from the Other Aerial Objects Using Deep Lar-based systems have limitations, including high costs, complex installation procedures, and limited accuracy in detecting small and low-flying drones. To address these limitations, this paper presents a novel drone detection system-based on deep learning using a modified You Only Look Once (YOLO)
48#
發(fā)表于 2025-3-29 20:23:32 | 只看該作者
49#
發(fā)表于 2025-3-30 00:59:36 | 只看該作者
Credit Card Fraud Detection System Using Support Vector Classifier growing issue of credit card fraud in online purchases. The suggested system analyses and pre-processes transaction data using the Support Vector Classifier algorithm, which effectively identifies fraudulent activity. The paper’s main objective is to show how the Support Vector Classifier algorithm
50#
發(fā)表于 2025-3-30 07:53:45 | 只看該作者
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