Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence.
As has been mentioned previously by Tanay, convolutional neural networks are mainly used for image processing, and usually for image classification. There are many reviews available online, however this one is very comprehensive:
convolution neural network will fall under the umbrella of deep learning. A neural network that has more number of hidden layers are concerned with deep learning. CNN makes wonders in image processing and computer vision. You can also try playing with tensor flow. Happy research :-)
CNN is one of the most remarkable form of ANN that is inspired by natural visual recognition phenomenon. There are innumerable applications of CNN in the field of image classification and pattern recognition.
To fully understand CNN, I would recommend you start from somewhere. First of all you need to understand linear/logistic regression. You then proceed with ANN and finally CNN.
To my best knowledge, ANN is two or more linear regression put together to form neurons with activation function at the end for prediction and CNN is much more of attaching ANN (fully connected layer) after the feature extraction (which is usually the combination of convolution and pooling layers).
Mainly for image processing and computer vision, however can be further explore for many other purposes. I think you've got enough links for review article. And don't forget " You can also try playing with tensor flow. Happy research :-) " by Anurekha Gopinathan.
The CNN is a type of Deep Neural Networks (DNN) that consists of many layers such as the Conv layers, Pooling layer, and the fully-connected layer. It mainly used for image classification purposes. The application can be in Robotics, Machine vision, IoT,....etc.
If you are interested in implementing the CNN on FPGA or ASIC hardware platform then i hope you can read my 5 recent publications. I hope they will help you.