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https://github.com/iremcatak/imageclassificationcnn

Image Classification with CNN and Python
https://github.com/iremcatak/imageclassificationcnn

cnn image-classification python3

Last synced: 14 days ago
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Image Classification with CNN and Python

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README 

        
# ImageClassificationCNN

Image Classification with CNN and Python

# Dataset Name: 

The CIFAR-10 dataset

# Dataset Link:

http://www.cs.toronto.edu/~kriz/cifar.html [1]

# Note:

The CIFAR-10 is labeled subsets of the 80 million tiny images dataset. They were collected by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. [1]

# Content

The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain more images from one class than another. Between them, the training batches contain exactly 5000 images from each class. [1]



# METHOD

In this project I worked with Anaconda and Jupyter Notebook (6.4.8). I used Python 3. I applied CNN (Convolutional Neural Network) to the CIFAR-10 Dataset. Also I used tensorflow and keras  libraries.



# What is CNN  (Convolutional Neural Network) ?

A convolutional neural network (CNN) is a type of artificial neural network used in image recognition and processing that is specifically designed to process pixel data. 

CNNs are powerful image processing, artificial intelligence (AI) that use deep learning to perform both generative and descriptive tasks, often using machine vison that includes image and video recognition, along with recommender systems and natural language processing (NLP). 

A neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Traditional neural networks are not ideal for image processing and must be fed images in reduced-resolution pieces. CNN have their “neurons” arranged more like those of the frontal lobe, the area responsible for processing visual stimuli in humans and other animals. The layers of neurons are arranged in such a way as to cover the entire visual field avoiding the piecemeal image processing problem of traditional neural networks. 

A CNN uses a system much like a multilayer perceptron that has been designed for reduced processing requirements. The layers of a CNN consist of an input layer, an output layer and a hidden layer that includes multiple convolutional layers, pooling layers, fully connected layers and normalization layers. The removal of limitations and increase in efficiency for image processing results in a system that is far more effective, simpler to trains limited for image processing and natural language processing. [2]    

# What is Tensorflow ?

TensorFlow is a Python-friendly open source library for numerical computation that makes machine learning and developing neural networks faster and easier. [3]

# What is Keras ?

Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library. [4]



# REFERENCES

1.Toronto University. “CIFAR-10 and CIFAR-100 datasets”. 

http://www.cs.toronto.edu/~kriz/cifar.html 

2.TechTarget. “What is convolutional neural network?”  

https://www.techtarget.com/searchenterpriseai/definition/convolutional-neural-network 

3.InfoWorld. “What is Tensorflow”.  

https://www.infoworld.com/article/3278008/what-is-tensorflow-the-machine-learning-library-explained.html 

4.Wikipedia. “Keras”.  

https://en.wikipedia.org/wiki/Keras