An AI model trained to determine the freshness of fruits and vegetables in an input image

它可以识别苹果是否腐烂，并给出详细的新鲜度分析

Our website for Bangkit Capstone Project that can knowing the level of ripeness of fruits

🖥️ Explore 20 hands-on experiments to master RISC-V computer architecture concepts using the Ripes simulator for effective learning.

Fruits freshness classifier with EfficientNet trained on Spoiled and fresh fruit inspection dataset, currently available for bananas, apples, and oranges

FreshCheck AI is a deep learning–based Streamlit application that classifies fruit images as fresh or spoiled using a pretrained ResNet-50 model. It demonstrates an end-to-end transfer learning pipeline, from data preparation and validation to real-time inference.

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

A CNN-based image classification system to automatically detect banana ripeness (Ripe vs. Unripe) using images. Trained on a Kaggle fruit dataset, this project provides an AI tool for easy and accurate freshness assessment.

Detecting the freshness using Ethylene Sensor Data using Machine Learning Models