This project is about Fruits-Vegetables classification application which is built using Deep Learning + Streamlit.

Fruit Classifier (Support Vector Machine vs KNN) using thresholding and Intensity Rescaling

Mobile application developed for detecting quality of fruits.

利用深度学习实现花果图像识别； Flower and fruit image recognition using deep learning

Low-cost industrial fruit classifier. uses state-of-the-art artificial vision technology to accurately and efficiently sort and grade fruits. The system is capable of identifying and distinguishing between different types and sizes of fruits

Fruit Classification using TensorFlow-Keras on Fruits 360 dataset

Clustering Fruits 360 dataset with deep feature extraction

Predict food (Fruits and Vegetables) images using Python

An Api thats collects data from an image and returns the descriptive properties

This is the same one as before, but I use deep learning

Fruit Classification using CNN

Fruit image classifier made with Keras VGG19 transfer learning and flask.

This is my assignment 3 recognition system

This repository contains the code related to the paper "Stop overkilling simple tasks with black-box models, use more transparent models instead"

Artificial Neural Network in Web Assembly, C++ Core & Interactive Website.

Machine Learning with Streamlit Python

Ripeness Palm Oil with deep learning model

Using Alexnet Architecture for Multiclass Fruit Classification

Página de apresentação do projeto de frutas e vegetais

FruitNutritionDetector: FastAPI-based API for Fruit Detection and Nutritional Information Retrieval using ImageAI and USDA API. Detect fruits from images and fetch detailed nutritional data.