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Automatic Eye Cataract Detection Using YOLOv8
Automatic Eye Cataract Detection is an AI-based tool leveraging YOLOv8 for precise and quick cataract diagnosis, enhancing efficiency and accuracy in eye care.
Crop Disease Detection Using YOLOv8
This project utilizes YOLOv8 to build a crop disease detection and classification system in Google Colab. The system processes images and videos to identify diseases, providing an interactive interface for real-time analysis using Gradio.
Vegetable classification with Parallel CNN model
This tutorial on Vegetable Classification using Machine Learing, guides you through automating the sorting process, improving quality control, and enhancing efficiency in agriculture and food industries.
Banana Leaf Disease Detection using Vision Transformer model
Banana Leaf Disease Detection leverages Deep Learning and Computer Vision to identify plant diseases early, helping farmers protect their crops, improve cultivation, and reduce losses with smarter, more sustainable farming methods.
Leaf Disease Detection Using Deep Learning
Our project uses deep learning to detect leaf diseases from images. By training models like VGG16 and EfficientNet on a robust dataset, we accurately diagnose plant conditions, aiding farmers in early disease detection and promoting healthier crops.
Glaucoma Detection Using Deep Learning
Glaucoma Detection Using Deep Learning uses AI to find early signs of glaucoma in eye images. This helps doctors diagnose the disease quickly and prevent vision loss.
Blood Cell Classification Using Deep Learning
Our Blood Cell Classification project uses CNN, EfficientNetB4, and VGG16 models to correctly sort blood cell images. This reduces up and improves the accuracy of research, which helps doctors make better decisions.
Skin Cancer Detection Using Deep Learning
Skin Cancer Detection project leverages advanced deep learning models, including CNN, DenseNet121, and EfficientNetB4, to accurately classify skin cancer images. This initiative aims to improve early diagnosis and patient outcomes.
Cervical Cancer Detection Using Deep Learning
Our Cervical Cancer Analysis project leverages the power of EfficientNetB0 to accurately classify different types of cervical cells. This initiative aims to enhance early cancer detection and improve patient outcomes through advanced AI technology.
Nutritionist Generative AI Doctor using Gemini
Get a complete overview of Generative AI, covering models, use cases, benefits, limitations, tools, ethics, and industry applications.
Chatbots with Generative AI Models
Create advanced chatbots and AI projects with GPT-3.5-turbo and GPT-4. Perfect the art of designing human-like interactions using detailed code examples.
Insurance Pricing Forecast Using XGBoost Regressor
This project builds an XGBoost Regressor to predict healthcare costs, ensuring insurance profitability. We'll compare it with a linear regression baseline and learn to communicate results effectively to non-technical stakeholders.