food-quality

Conveyor fruit inspection — grading in control zone C. Win + Linux x64 demos · Nim · ONNX Runtime · eval 0.10.0

Finding similar foods to change the unhealthy diet using Knowledge Graphs

Tilapia Fish Freshness Evaluation by Gill Color Using YOLOv3 and GrabCut Algorithm for Image Segmentation and Utilization of RGB Channels for Feature Extraction

Code, data, and results for Richmond et al. Individual herbivores manage risk differently: Stoichiometric distribution models with snowshoe hares. Manuscript published at Journal of Mammalogy.

An AI-powered web application that classifies fruits as fresh or rotten using MobileNetV2 transfer learning, TensorFlow, Flask, and computer vision techniques.

AI-powered Fresh vs Rotten Fruit & Vegetable Detection System built with TensorFlow, Keras, Flask, and Computer Vision for real-time image classification.

CNN-based potato quality classification system using MobileNetV2. Classifies potatoes as Healthy, Green, or Rotten with a simulation-based pipeline.

Blueberry instance segmentation and multi-stage quality classification with trained models and Windows inference app.

Open-source real-time milk adulteration detection system using Arduino (pH, turbidity, temp, gas sensors), a Node.js bridge server, and a React Native/Expo mobile app. Get a live SAFE/ADULTERATED verdict on your phone.

Leakage-safe estimation of shell-egg storage time from portable NIR spectra, with egg-disjoint validation, chemometric models and documented computational analyses.

Food quality classification project using Vision Transformer to classify images as fresh or spoiled.

This is the dataset that we used in Meat Quality Assessment based on Deep Learning.

Predicting white wine quality from physicochemical features using Random Forest classification in R. Includes EDA with correlation heatmap, scatterplot matrix, and violin plots. Achieved 69% accuracy on UCI Wine Quality dataset.

A project for NIR-based food quality modeling using PLS or ANN based on MATLAB or Python

Deep learning-based rice grain quality analysis system using YOLOv8 and CNNs for rice detection, variety classification, defect identification, and automated quality grading.

🍎 Predicts freshness of fruits & vegetables using ShuffleNet V2 with transfer learning. Achieves 97.25% accuracy — outperforms ResNet-18, MobileNetV2 & EfficientNet. PyTorch · Tkinter GUI

AI-powered food freshness classifier using Python and machine learning.

IoT food quality monitor: ESP32 sensors (gas, alcohol, pH, temperature, humidity) plus a CNN camera model, with a live MQTT dashboard that predicts spoilage and triggers alerts.