This project classifies fruit quality into five levels (Fresh to Rotten) using image preprocessing, data augmentation, and clustering (K-Means, Agglomerative, DBSCAN). Deep learning models are trained on clustered data, with AlexNet + Agglomerative Clustering achieving top results (Acc: 0.84, F1: 0.83).

This project classifies fruit quality into five levels (Fresh to Rotten) using image preprocessing, data augmentation, and clustering (K-Means, Agglomerative, DBSCAN). Deep learning models are trained on clustered data, with AlexNet + Agglomerative Clustering achieving top results (Acc: 0.84, F1: 0.83).

This project classifies fruit quality into five levels (Fresh to Rotten) using image preprocessing, data augmentation, and clustering (K-Means, Agglomerative, DBSCAN). Deep learning models are trained on clustered data, with AlexNet + Agglomerative Clustering achieving top results (Acc: 0.84, F1: 0.83).

This project classifies fruit quality into five levels (Fresh to Rotten) using image preprocessing, data augmentation, and clustering (K-Means, Agglomerative, DBSCAN). Deep learning models are trained on clustered data, with AlexNet + Agglomerative Clustering achieving top results (Acc: 0.84, F1: 0.83).

AI-powered food freshness detection using deep learning

AI-powered food freshness detection using deep learning

AI-based food detection and freshness analysis system that identifies food from images using deep learning and evaluates freshness. The system also uses Google Gemini to generate recipes, nutritional information, and food insights. Built with React, Node.js, FastAPI, and computer vision models.

Food Freshness Detection using CNN is a deep learning project that classifies food images as fresh or rotten. The model is trained using a Convolutional Neural Network and deployed with a Gradio interface, allowing users to upload an image and instantly receive a freshness prediction.

🚀 Fruits And Vegetables Freshness Detection using Machine Learning I’m excited to share my latest Machine Learning project where I built an end-to-end system to detect whether food is Fresh or Rotten using Deep Learning.

Built a real-time egg quality detection system using YOLOv8, classifying eggs as fresh or spoiled through a live camera feed. Trained on a custom dataset with data augmentation and early stopping for optimized, CPU-compatible inference — demonstrating practical deep learning applications in food quality control and agricultural automation.