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Papers tagged with "Lstm"
A Privacy-Preserving Federated Learning Framework With Dual Explainability For Hybrid CNN–LSTM Based Anomaly Detection In IoT Network Traffic
Intrusion Detection Systems (IDS) For The Internet Of Things Face A Three-way Tension: Deep Models Detect Attacks Accurately But Behave As Opaque Black Boxes, Centralised Training Pipelines Require Raw Traffic To Be Exported From Every Devi...
ML-Based Anomaly Detection In Healthcare Systems Using ESP32 Microcontroller
Continuous Monitoring Of Patient Vital Signs Through Wireless Body Area Networks (WBANs) Is Increasingly Central To Modern Healthcare, Yet Validating Anomaly-detection Pipelines On Real Hospital Networks Is Costly, Ethically Constrained, An...
Federated Learning And Explainable Artificial Intelligence For Intrusion Detection In IoT Networks: A Review
The Rapid Enlargement Of The Internet Of Things Has Turned Billions Of Weakly Protected Devices Into An Attractive Attack Surface, And Machine-learning Intrusion Detection Has Become The Default Defensive Answer. Three Difficulties, However...
Physical Violence Detection Using Key Framing
The Physical Violence Detection Using Key Framing App Is An AI-based Android Application Designed To Detect Violent Activities From Video Footage Using Intelligent Frame Analysis. The System Focuses On Identifying Suspicious Physical Action...
AI-Driven Price Prediction System For Direct Farmer-to- Market Consumer Agricultural Market
Farmers Who Sell Directly To Consumers Through Digital Platforms Often Have No Idea What Price To Charge For Their Produce. They Rely On Heuristic Judgment And Informal Market Signals, Or Whatever Their Neighbor Charged Last Week. This Leav...
Design And Implementation Of An AI-Powered Mental Health Chatbot Using Machine Learning, NLP, And Deep Learning
Mental Health Disorders Affect Over One Billion People Globally, Yet Timely Professional Support Remains Limited. This Paper Presents MindCare, An AI-powered Mental Health Chatbot Integrating Natural Language Processing (NLP), Machine Learn...
AI Based Cyber Threat Prediction
The AI-Based Cyber Threat Prediction System Improves Cybersecurity Using Artificial Intelligence, Machine Learning, And Deep Learning Techniques. The System Continuously Monitors Network Traffic, System Logs, And User Activities To Identify...
A HYBRID STOCK PRICE FORECASTING SYSTEM USING ARIMA, LSTM, AND SENTIMENT ANALYSIS
The Accurate Forecasting Of Stock Prices Remains One Of The Most Persistent And Challenging Problems In Quantitative Finance, Owing To The Inherently Noisy, Nonstationary, And Nonlinear Nature Of Financial Time Series. Traditional Foreca...
HYBRID MACHINE LEARNING AND DEEP LEARNING-BASED VPN NETWORK TRAFFIC ANOMALY DETECTION SYSTEM
The Rapid Growth Of Internet Usage And The Widespread Adoption Of Virtual Private Networks (VPNs) Have Significantly Enhanced Secure Communication, But Have Also Introduced New Challenges In Detecting Cyber Threats Hidden Within Encrypted T...
Digital Twin Driven Hybrid LSTM And Isolation Forest Framework For Predictive Failure Detection And Autonomous Self Healing In Servers
Cloud Server Infrastructures Form The Foundation For Technical Services, Where The Services Will Be Highly Available, Critical For Business Continuity And User Satisfaction. Traditional Systems Notify The User After The Failures Had Occurre...
AI-Powered Inventory Management System- Ezze Buy
This Paper Presents The Design, Architecture, And Full-stack Implementation Of EzzeBuy, A Web-based AI-powered Inventory Management And Sales Prediction Platform. The System Integrates A Long Short-Term Memory (LSTM) Neural Network Backend...
AI-Driven Banking Security Monitoring System
Banking Environments Consistently Rank Among The Most Security-critical Operational Domains, Where Institutions Must Safeguard Financial Assets, Sensitive Customer Information, And Personnel Against Theft, Fraud, And Unauthorized Access. Em...
AI-Powered Twitter Content Moderation Using SBERT, CNN And Bi-LSTM With Severity-Based Alert System
Social Media Platforms Such As Twitter (now X) Generate Large Volumes Of Real-time Content, Including Spam, Malicious Links, And Harmful Messages. The Rapid Spread Of Such Content Poses Significant Challenges For Manual Moderation Due To Hi...
Privacy-Preserving Multiple Payment Fraud Detection Using LSTM-based Federated Learning.
This Paper Presents A Privacy-preserving Framework For Multiple Payment Fraud Detection Using Long Short-Term Memory (LSTM) And Federated Learning. The Model Captures Temporal Patterns In Transaction Data To Identify Fraudulent Activities E...
Cyber Threat Intelligence System Using CNN-LSTM Deep Learning Model
Cyber Threat IntelligenceThe Rapid Evolution Of Cyber Threats, Including Malware, Phishing Attacks, Distributed Denial Of Service (DDoS), And Advanced Persistent Threats, Has Made Traditional Security Mechanisms Less Effective. Conventional...