CNN-Based Models Final Year Projects for BE, BTech, ME, MSc, MCA and MTech final year engineering students. These CNN-Based Models projects give practical experience and help complete final-year submissions. All projects follow IEEE standards and each project includes source code, project thesis report, presentation, project execution and explanation.

CNN-Based Models Final Year Projects

A CNN-Model to Classify Low-Grade and High-Grade Glioma From MRI Images

This project focuses on identifying how severe a brain tumor is using MRI images. It uses a light and fast deep learning model to classify tumors into low-grade or high-grade groups. The model is trained on public medical datasets and data from a local hospital. It shows very high accuracy compared to other popular deep learning models.
Application of X-Ray Imaging and Convolutional Neural Networks in the Prediction of Tomato Seed Viability

This project focuses on predicting whether tomato seeds will grow successfully without damaging them. The researchers used X-ray images of seeds to check their internal structure. They created two prediction models: one based on image analysis and another using a type of artificial intelligence called a convolutional neural network (CNN). The CNN model was more accurate, achieving 86% accuracy, showing that this method can help farmers and scientists test seed quality quickly and safely.

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CNN-Based Models Project Synopsis & Presentation

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CNN-Based Models Final Year Projects with Source Code