Fraud Detection in Payments Transactions: Overview of Existing Approaches and Usage for Instant Payments by Alexander Diadiushkin, Kurt Sandkuhl, Alexander Maiatin

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Unveiling the Efficacy of AI-based Algorithms in Phishing Attack Detection by Tajamul Shahzad, Kashif Aman

“…Moreover, the paper shows how different AI techniques have been employed in multiple studies to detect and address phishing attacks. …”
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Interacting with fallible AI: is distrust helpful when receiving AI misclassifications? by Tobias M. Peters, Ingrid Scharlau

“…We discuss the implications of our results for the usage of disclaimers before interacting with AI, as prominently used in current LLM-based chatbots, and for trust and distrust research.…”
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A DIGITAL QUALITY ASSESSMENT OF BAMBOOSHOOTS.AI FOR HARVEST AND PEST DETECTION by Charlot L. Maramag, Thelma D. Palaoag

“…This research offered an in-depth evaluation of "BambooShoots.AI," a platform aiding bamboo cultivators in harvest timing and pest detection. …”
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Empowering Smallholder Farmers with UAV-Based Early Cotton Disease Detection Using AI by Halimjon Khujamatov, Shakhnoza Muksimova, Mirjamol Abdullaev, Jinsoo Cho, Cheolwon Lee, Heung-Seok Jeon

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Post-Hoc Categorization Based on Explainable AI and Reinforcement Learning for Improved Intrusion Detection by Xavier Larriva-Novo, Luis Pérez Miguel, Victor A. Villagra, Manuel Álvarez-Campana, Carmen Sanchez-Zas, Óscar Jover

“…The massive usage of Internet services nowadays has led to a drastic increase in cyberattacks, including sophisticated techniques, so that Intrusion Detection Systems (IDSs) need to use AP technologies to enhance their effectiveness. …”
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Generative AI in Intrusion Detection Systems for Internet of Things: A Systematic Literature Review by Zhe Deng, Ants Torim, Sadok Ben Yahia, Hayretdin Bahsi

“…By harnessing the capabilities of generative AI, it is feasible to augment intrusion detection models, allowing for more robust and adaptive security solutions in IoT environments. …”
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Interpretable deep learning for gastric cancer detection: a fusion of AI architectures and explainability analysis by Junjie Ma, Fang Yang, Rong Yang, Yuan Li, Yongjing Chen

“…IntroductionThe rise in cases of Gastric Cancer has increased in recent times and demands accurate and timely detection to improve patients' well-being. The traditional cancer detection techniques face issues of explainability and precision posing requirement of interpretable AI based Gastric Cancer detection system.MethodThis work proposes a novel deep-learning (DL) fusion approach to detect gastric cancer by combining three DL architectures, namely Visual Geometry Group (VGG16), Residual Networks-50 (RESNET50), and MobileNetV2. …”
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Sign language detection dataset: A resource for AI-based recognition systemsMendeley Data by Bindu Garg, Manisha Kasar, Priyanka Paygude, Amol Dhumane, Srinivas Ambala, Jitendra Rajpurohit, Abhay Sharma, Vidula Meshram, Amber Vats, Achyut Kashyap

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DeSFAM: An Adaptive eBPF and AI-Driven Framework for Securing Cloud Containers in Real Time by Sehar Zehra, Hassan Jamil Syed, Fahad Samad, Ummay Faseeha

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Toward Compliance and Transparency in Raw Material Sourcing With Blockchain and Edge AI by Abderrahim Khiari, Anas Osman, Massimo Vecchio, Mattia Antonini, Miguel Pincheira

“…To address this gap, we propose the Raw Material Radar (RMR) framework, centered on a smart barrel that integrates IoT sensing, edge AI processing, and blockchain-based record-keeping. …”
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Generative AI-driven edge-cloud system for intelligent road infrastructure inspection by Naveed Ejaz, A.B.M. Bodrul Alam, Salimur Choudhury

“…The Edge AI Module, built on MobileNetV3, performs real-time anomaly detection and generates concise reports with GPS-tagged severity information. …”
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Edge-AI Enabled Wearable Device for Non-Invasive Type 1 Diabetes Detection Using ECG Signals by Maria Gragnaniello, Vincenzo Romano Marrazzo, Alessandro Borghese, Luca Maresca, Giovanni Breglio, Michele Riccio

“…The hardware integrates high-performance electronics with low power consumption, demonstrating the feasibility of deploying Edge-AI for non-invasive, real-time diabetes detection in resource-constrained environments. …”
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First-of-its-kind AI model for bioacoustic detection using a lightweight associative memory Hopfield neural network by Andrew Gascoyne, Wendy Lomas

“…In this paper, we present an alternative AI model which has the potential to help alleviate this problem. …”
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CryptoDNA: A Machine Learning Paradigm for DDoS Detection in Healthcare IoT, Inspired by Cryptojacking prevention Models by Zag ElSayed, Nelly Elsayed, Ahmed Abdelgawad

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OpenTrack: a Sensor for Monitoring the Usage of Territory by D. Strigaro, A. Rollandi, M. Cannata

“…In the Mendrisio district (Switzerland), we deployed a low-cost, AI-powered sensor to monitor pedestrian and vehicle flows in different seasons. …”
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On the usage of artificial intelligence in leprosy care: A systematic literature review. by Hilson Gomes Vilar de Andrade, Elisson da Silva Rocha, Kayo H de Carvalho Monteiro, Cleber Matos de Morais, Danielle Christine Moura Dos Santos, Dimas Cassimiro Nascimento, Raphael A Dourado, Theo Lynn, Patricia Takako Endo

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A Secure IIoT Environment That Integrates AI-Driven Real-Time Short-Term Active and Reactive Load Forecasting with Anomaly Detection: A Real-World Application by Md. Ibne Joha, Md Minhazur Rahman, Md Shahriar Nazim, Yeong Min Jang

“…The Industrial Internet of Things (IIoT) revolutionizes both industrial and residential operations by integrating AI (artificial intelligence)-driven analytics with real-time monitoring, optimizing energy usage, and significantly enhancing energy efficiency. …”
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EnsembleXAI-Motor: A Lightweight Framework for Fault Classification in Electric Vehicle Drive Motors Using Feature Selection, Ensemble Learning, and Explainable AI by Md. Ehsanul Haque, Mahe Zabin, Jia Uddin

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FRAUD-X: An Integrated AI, Blockchain, and Cybersecurity Framework With Early Warning Systems for Mitigating Online Financial Fraud: A Case Study From North Macedonia by Bekim Fetaji, Majlinda Fetaji, Affan Hasan, Shpetim Rexhepi, Goce Armenski

“…This paper introduces FRAUD-X, a unified framework merging artificial intelligence (AI)–based anomaly detection, blockchain-driven transaction verification, cybersecurity intrusion detection, and real-time early warning mechanisms into a single pipeline. …”
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