'
\nOpen source projects on flower classification? Are you kidding me? You want me to do what with my free time? Classification of flowers is hard enough work as it is, without having to worry about some open source project that may or may not be finished.
\nBut if you insist…
\nOkay, okay. I'll list a few of the more popular open source projects on flower classification.
\nJust don't get mad at me if they're not perfect. After all, no one really knows how to classify flowers perfectly, do they?
\n\nUdacity Data Science Nanodegree program, deep learning on Pytorch, image classification (flowers)
\n
It uses pytorch.
\nIt has 2 python files
\n\nPyTorch Scholarship Challenge from Facebook / Deep Learning / CNN / Flowers Classification
\n
It uses pytorch.
\n\n\nClassification of flower images into respective classes using Deep Learning and Evolutionary Optimization.
\n
It uses pytorch.
\nIt has 2 notebooks
\n\nFine-tuning InceptionV3 for flowers classification. From Coursera's Advanced Machine Learning - Intro to Deep Learning This repository contains the code used for the flowers classification project in the \"Advanced Machine Learning - Intro to Deep Learning\" course on Coursera.
\n
It uses tensorflow.
\nIt has 1 python file
\n\nImage Classification system built with PyTorch using Deep Learning concepts in order to recognize different species of flowers.
\n
It uses pytorch.
\nIt has 2 python files
\n\nClassification of 102 flower species with Deep Learning
\n
It uses pytorch.
\n\n\nUse of various deep learning models to classify flowers. Models are implemented from scratch in PyTorch using only telegraphic data.
\n
It uses pytorch.
\n\n\nNow Classify Flower pictures with a Deep Learning Model. Model is trained from transfer learning using VGGnet.
\n
It uses tensorflow.
\nIt has 1 python file
\n\nDeveloped an android mobile app (GreenFinder), trained, and evaluated two deep learning image classification models fThe article discusses the development of an android mobile app (GreenFinder) for identifying plants using deep learning image classification models. The app was trained and evaluated on two different data sets: a data set of images of plants from the internet and a data set of images of plants from the University of Maryland Herbarium. The results of the evaluation showed that the deep learning models were able to achieve an accuracy of up to 97.5% for the identification of plants from the internet data set and an accuracy of up to 97.8% for the identification of plants from the University of Maryland Herbarium data set.
\n
It uses tensorflow.
\n\n\nFlowers Image Classification using Deep Learning. This final project in the Deep Learning section is part of Udacity's Machine Learning Engineer Nanodegree.
\n
It uses tensorflow.
\nIt has 3 python files
\n\nA deep learning-based flower classification system
\n
It uses pytorch.
\nIt has 2 python files
'
\nOpen source projects on flower classification? Are you kidding me? You want me to do what with my free time? Classification of flowers is hard enough work as it is, without having to worry about some open source project that may or may not be finished.
\nBut if you insist…
\nOkay, okay. I'll list a few of the more popular open source projects on flower classification.
\nJust don't get mad at me if they're not perfect. After all, no one really knows how to classify flowers perfectly, do they?
\n\nUdacity Data Science Nanodegree program, deep learning on Pytorch, image classification (flowers)
\n
It uses pytorch.
\nIt has 2 python files
\n\nPyTorch Scholarship Challenge from Facebook / Deep Learning / CNN / Flowers Classification
\n
It uses pytorch.
\n\n\nClassification of flower images into respective classes using Deep Learning and Evolutionary Optimization.
\n
It uses pytorch.
\nIt has 2 notebooks
\n\nFine-tuning InceptionV3 for flowers classification. From Coursera's Advanced Machine Learning - Intro to Deep Learning This repository contains the code used for the flowers classification project in the \"Advanced Machine Learning - Intro to Deep Learning\" course on Coursera.
\n
It uses tensorflow.
\nIt has 1 python file
\n\nImage Classification system built with PyTorch using Deep Learning concepts in order to recognize different species of flowers.
\n
It uses pytorch.
\nIt has 2 python files
\n\nClassification of 102 flower species with Deep Learning
\n
It uses pytorch.
\n\n\nUse of various deep learning models to classify flowers. Models are implemented from scratch in PyTorch using only telegraphic data.
\n
It uses pytorch.
\n\n\nNow Classify Flower pictures with a Deep Learning Model. Model is trained from transfer learning using VGGnet.
\n
It uses tensorflow.
\nIt has 1 python file
\n\nDeveloped an android mobile app (GreenFinder), trained, and evaluated two deep learning image classification models fThe article discusses the development of an android mobile app (GreenFinder) for identifying plants using deep learning image classification models. The app was trained and evaluated on two different data sets: a data set of images of plants from the internet and a data set of images of plants from the University of Maryland Herbarium. The results of the evaluation showed that the deep learning models were able to achieve an accuracy of up to 97.5% for the identification of plants from the internet data set and an accuracy of up to 97.8% for the identification of plants from the University of Maryland Herbarium data set.
\n
It uses tensorflow.
\n\n\nFlowers Image Classification using Deep Learning. This final project in the Deep Learning section is part of Udacity's Machine Learning Engineer Nanodegree.
\n
It uses tensorflow.
\nIt has 3 python files
\n\nA deep learning-based flower classification system
\n
It uses pytorch.
\nIt has 2 python files