Reconnaissance des fruits en utilisant les modéles de deep learning: Resnet, Vgg16, MobileNetV2, CNN personalisé
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Updated
Feb 23, 2021
Reconnaissance des fruits en utilisant les modéles de deep learning: Resnet, Vgg16, MobileNetV2, CNN personalisé
A boring 33 class fruit classifier.
CNN is used to build a deep learning model for the prediction of fruits. Total of 31 different fruits classes are there
Classification using fruits360 from kaggle, and applying ML techniques
Image segmentation model for checking apple quality using UNet model architecture on TensorFlow along with AWS SageMaker deployment.
Machine Learning with Streamlit Python
Robust fruit detection system using YOLOv4.
AI-Driven Smart Fruit Classifier
This is the same one as before, but I use deep learning
Fruit image classifier made with Keras VGG19 transfer learning and flask.
This is my assignment 3 recognition system
Fruit Classification using CNN
Artificial Neural Network in Web Assembly, C++ Core & Interactive Website.
This repository contains the code related to the paper "Stop overkilling simple tasks with black-box models, use more transparent models instead"
Página de apresentação do projeto de frutas e vegetais
Ripeness Palm Oil with deep learning model
Using Alexnet Architecture for Multiclass Fruit Classification
An Api thats collects data from an image and returns the descriptive properties
Clustering Fruits 360 dataset with deep feature extraction
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