Convolutional Neural Network

Learn the fundamental aspects to design a convolutional neural network architecture by providing steps of modeling and c

An overview of the deep learning field

Details to design a Convolutional Neural Network architecture

Limitation, future and challenges of convolutional neural networks

Basic math (Convolution, matrix, probability)

Basic knowledge of image processing

which means endowed this machine by intelligence, unlike, as all known, the habitual intelligence are exhibited by humans and animals. Therefore, in this course, we investigate the mimicking of human intelligence on machines by introducing a modern algorithm of artificial intelligence named convolutional neural network which is a technique of deep learning for computers to make the machine learn and expert. In this course, we present an overview of deep learning in which, we introduce the notion and classification of convolutional neural networks. We gives also the definition and the advantages of CNNs. In this course, we provide the tricks to elaborate your own architecture of CNN and the hardware and software to design a CNN model. In the end, we present the limitation and future challenges of CNN.

The essential points tackled in this course are given as follow:

- What is deep learning

- Why computational Intelligence algorithms are used

- Biomimetics inspiration of CNN from brain

- Classification of deep learning (CNN)

- The kinds of deep learning algorithms

- Definition of convolutional neural networks

- Advantages of Convolutional Neural Network

- The aim of CNN

- Architecture of CNN

- Training and optimization of CNN parameters

- Hardware material used for CNN

- Software used for deep learning

- Famous CNN architecture

- Application of CNN

- Limitation of CNN

- Future and challenges of convolutional neural networks

- Conclusions

Eeering Acads

Passion and Interest for learning concepts of artificial intelligence

University students of Computer Science



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