Python
Advancing Fake News Detection: Hybrid Deep Learning With FastText and Explainable AI
Advancing Ovarian Cancer Diagnosis Through Deep Learning and Explainable AI: A Multiclassification Approach
Agri – IoT A farm monitoring and automation system using internet of things
Agri-4-All: A Framework for Blockchain Based Agricultural Food Supply Chains in the Era of Fourth Industrial Revolution
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.
Agricultural Loan Recommender System – A Machine Learning Approach
AI and Digital Twins Transforming Healthcare IoT
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.
An Analysis of Li-Fi based Prevalent Automated Billing Systems in Shopping Malls
An Approach to Control the PC with Hand Gesture Recognition using Computer Vision Technique
An Edge-Based Digital Twin Framework for Connected and Autonomous Vehicles: Design and Evaluation
Aim:
The aim of this project is to design and implement an edge-based digital twin system for monitoring and controlling the performance of a connected vehicle. Using sensors like the LM35 for engine temperature, IR sensors for speed measurement, and push buttons for speed control, the system optimizes real-time vehicle operations. It integrates the vehicle's real-time data into a digital twin for simulation, performance evaluation, and diagnostics. This approach enhances vehicle efficiency, safety, and real-time decision-making through continuous monitoring and control.
