Python
A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning with Explainable AI
A Novel Approach Based on Quantum Key Distribution Using BB84 and E91 Protocol for Resilient Encryption and Eavesdropper Detection
Aim:
To implement a secure, interactive, and educational Quantum Key Distribution (QKD) system using the SARG04 algorithm simulated with Qiskit and deployed as a full-stack web application (Flask + React + MySQL) for demonstrating real-time quantum key sharing and eavesdropper detection between Alice, Bob, and Eve.
A Novel Dangerous Goods Detection Network Based on Multi-Layer Attention Mechanism in X-Ray Baggage Images
A Novel Integrated Approach for Stock Prediction Based on Modal Decomposition Technology and Machine Learning
A Web-Based Interface That Leverages Machine Learning to Assess an Individual’s Vulnerability to Brain Stroke
Adaptive Defense Zero-Day Attack Detection in NIDS with Deep Reinforcement Learning
Advanced Analysis of Learning-Based Spam Email Filtering Methods Based on Feature Distribution Differences of Dataset.
Advanced Heart Attack Risk Prediction Using Stacked Hybrid Machine Learning
Advanced YOLO DeepSort Based System for Drainage Pipeline Defects Intelligent Detection
Advancing Fake News Detection: Hybrid Deep Learning With FastText and Explainable AI
Agricultural Futures Trading Decision Using AI Agent with Multiscale Candlestick Analysis
The aim to build an AI system that helps traders make better decisions during unpredictable and high-volatility market periods. To automate chart reading and reduce human error by using AI to analyze patterns and market behavior. It create a smarter trading assistant that can learn from past results and provide more reliable buy/sell guidance.
AI-Generated vs. Human Text: Introducing a New Dataset for Benchmarking and Analysis
Aim: The aim of this project is to enhance the ability to distinguish between AI-generated and human-authored text by utilizing a fine-tuned BERT classifier. This approach emphasizes contextual understanding and deep language representation to outperform traditional machine learning systems in identifying AI-generated content.