Abstract Telecommunication fraud continues to rise, costing billions globally each year. Traditional detection methods often fail to keep pace with new and evolving threats. This project introduces an AI-based fraud detection systemRead More…
Abstract Vehicle-related violations like over-speeding contribute to around 25% of urban traffic accidents. These incidents increase global enforcement costs. Traditional detection systems often fail under low light, heavy traffic, or fast-moving vehicles.Read More…
Abstract Breast cancer ultrasound detection is a vital tool for early and accurate medical diagnosis. This study presents a deep learning-based system that classifies ultrasound images into three categories: benign, malignant, andRead More…
Abstract Traffic sign detection is essential for autonomous vehicles to navigate roads safely and accurately. While Convolutional Neural Networks (CNNs) are effective in identifying traffic signs, their high memory and processing requirementsRead More…
Abstract Traditional steganography methods struggle with outdated encryption and compression, leading to high computational costs, large key sizes, and weak resistance to modern steganalysis attacks. These drawbacks make conventional systems inefficient andRead More…
Abstract As healthcare systems become more digital, protecting patient data is more critical than ever. This project presents a secure patient data management system that combines AES-256 encryption with blockchain audit trails.Read More…
Abstract In the era of content overload, viewers often need to extract key insights from lengthy YouTube videos—especially when transcripts are missing or the language is unfamiliar. Smart Summarizer is an AI-poweredRead More…
Abstract Clustering sensor nodes is a smart way to design energy-efficient routing for Wireless Sensor Networks (WSNs). It helps improve network lifespan and reduces power consumption. However, cluster heads perform extra tasks,Read More…
Abstract Railway safety and operational efficiency heavily rely on accurate and cost-effective track inspections. Traditional manual inspection methods are time-consuming, error-prone, and struggle to keep pace with expanding rail infrastructure. To addressRead More…
