This project is for the Identification of Iris flower species is presented
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Updated
Sep 17, 2020 - Jupyter Notebook
This project is for the Identification of Iris flower species is presented
Flutter Android & iOS Flowers Recogniser App [Deep Learning & Machine Learning]
PyTorch Scholarship Challenge from Facebook / Deep Learning / CNN / Flowers Classification
encyclo-flower.com site
Automated flower species classification for generating honey-bee foraging maps from drone imagery
Classifying Flowers using Transfer Learning and Data Augmentation
Project based about a flower shop
Flowers classification app using Deep Neural Networks
Image Classification modelling for the Oxford-Flowers102 dataset. Looking at a model that predicts new flower images based on the already pre-trained categories, with relative high accuracy.
Simple flower classifier made with help of fastai and 17flowers dataset
In this Internship, I was given some tasks related to day-to-day problems we face in our practical life and how to evaluate those using machine learning models.
Used normal neural networks and convolutional neural networks in many many data like animals, fashion, flowers classification, and also temperature predictions and time-series. Have fun. BTW used tensorflow for the works.
The goal of this project is to study and implement VGG19 based classification model for Flowers' dataset.
Flower classification using CNNs
This Image Classification model helps you to recognized 102 kinds of flowers that are provided my Oxford University. I am using famous 102 oxford flower dataset.
🌷This project implements a Convolutional Neural Network (CNN) for classifying flower images into categories such as tulip, sunflower, roses, dandelions, and daisy.
Classifying Flowers on the basis of their images with the help of a simple CNN 🤖
This project uses a deep CNN for classifying images from the Flowers-102 dataset. I employed cross-entropy loss for accurate classification and AdamW optimizer for stable training. Data augmentation techniques like random flips and rotations are used to enhance model generalization.
Final Project of the AWS/Udacity AI & ML Scholarship Nanodegree
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