Precision Meets Innovation!
Featured ProjectSecure Data Sharing in Cloud Computing Using Revocable Storage Identity Based Encryption
This project implements a secure data sharing model in cloud computing environments using Revocable Storage Identity-Based Encryption (RS-IBE). The RS-IBE model ensures data confidentiality and reduces the workload on key authorities, enhancing scalability and security. Key technologies used include Java for backend logic, JavaScript for client-side scripting, HTML, CSS for frontend design, JSP for server-side processing, and MySQL for database management. This comprehensive approach effectively addresses data security challenges in cloud computing environments.
AI-Based ApplicationVirtual Mouse Hand Gesture Recognition Using OpenCV With Voice Assistant
This project develops an AI-based virtual mouse system using hand gesture recognition via OpenCV and MediaPipe, along with voice commands for enhanced user interaction. The system captures hand movements using a webcam and translates these into mouse actions, eliminating the need for physical mice. It supports commands such as left-click, right-click, scrolling, and drag-and-drop. Voice commands control system functionalities like opening and closing the virtual mouse, searching, and finding locations. This system improves human-computer interaction, making it especially useful in touchless environments. Key technologies used include Python, OpenCV, MediaPipe, and Speech Recognition.
Medical ApplicationAlzheimer's Disease Detection
This project innovates in the medical field by developing an accurate Alzheimer's disease detection system. Using Non-negative Matrix Factorization (NMF) for feature extraction and Support Vector Machine (SVM) for disease stage prediction, the system significantly improves diagnostic accuracy over traditional methods. The project leverages data from ADNI-1, ADNI-2, and OASIS datasets and utilizes Python for implementation. This advanced diagnostic tool aims to assist medical professionals in early and accurate detection of Alzheimer's disease, potentially improving patient outcomes.
Predictive ModelCurrency Price Prediction
This project focuses on predicting currency prices using advanced machine learning techniques. Utilizing Python, pandas for data manipulation, yfinance for financial data extraction, Prophet for time series forecasting, and Plotly for interactive visualizations, the model provides accurate and insightful currency price forecasts. This project highlights the integration of data analysis, feature engineering, and predictive modeling to deliver reliable financial predictions, aiding in informed decision-making for traders and investors.