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In the context of image recognition on CIFAR10 data, the following algorithms have been implemented and tested: Naive algorithm - Closest neighbor - Knn Sophisticated algorithm: From the article: "An Analysis of Single-Layer Networks in Unsupervised Feature Learning "

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In the context of image recognition on CIFAR10 data, the following algorithms have been implemented and tested: Naive algorithm - Closest neighbor - Knn Sophisticated algorithm: From the article: "An Analysis of Single-Layer Networks in Unsupervised Feature Learning "

Algorithme naïf de reconnaissance d'image

auteur

Akharaz Majid

Prerequisites

python3 numpy

Pour lancer la reconnaissance d'image :


Dans le dossier datasets à partir du terminal executer 
sh get_datasets.sh

puis: 


python3 k_nearest_neighbor.py
python3 Nearest_Neighbour.py


Pour lancer l'implémentation de l'article

auteur

Akharaz Majid

Prerequisites

python3 numpy

Pour lancer la reconnaissance d'image :


Dans le dossier datasets à partir du terminal executer 
sh get_datasets.sh

puis: 

Après avoir télécharger les données (si c'est pas déjà fait)
python3 article.py

ou 

executer le notebook
test.ipynb



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In the context of image recognition on CIFAR10 data, the following algorithms have been implemented and tested: Naive algorithm - Closest neighbor - Knn Sophisticated algorithm: From the article: "An Analysis of Single-Layer Networks in Unsupervised Feature Learning "

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