This project utilizes OpenCV, a popular computer vision library, to detect faces and eyes in images and videos. The goal is to provide a simple yet effective solution for detecting these key facial features in real-time.

This project aims to develop a system for the automated detection of plant diseases from images of leaves and providing suitable solutions to mitigate them. Leveraging image processing techniques, the system analyzes input leaf images, identifies diseases present, and offers recommendations for treatment or prevention.

The aim of this report is to provide an overview of the development and implementation of a real-time expression detection application using OpenCV (Open Source Computer Vision Library). The application accesses the video camera feed and employs computer vision techniques to detect various facial expressions such as happy, sad, angry, surprised.

Welcome to TIPS, the centralized project platform for engineering students! Whether you're looking to dive into advanced domains like Machine Learning, Artificial Intelligence, Blockchain, Web Development, Database, or many others, TIPS is your go-to destination.

Depression detection using machine learning is a vital area of research given the global burden of mental health disorders. This project explores two primary methodologies: leveraging depression quiz tests and analyzing sentences.

The area is facing high levels of air and soil pollution, posing risks to public health, ecosystems, and agriculture. Current monitoring efforts are inadequate and fail to address the link between air and soil quality.

Nyayaprabha is a beacon of hope for women seeking a safe and accessible platform to voice their concerns and fight for justice. It's not just a website, but a movement empowered by technology and empathy

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