  In the last few years, deep learning has led to very good performance on a
variety of problems, such as visual recognition, speech recognition and natural
language processing. Among different types of deep neural networks,
convolutional neural networks have been most extensively studied. Leveraging on
the rapid growth in the amount of the annotated data and the great improvements
in the strengths of graphics processor units, the research on convolutional
neural networks has been emerged swiftly and achieved state-of-the-art results
on various tasks. In this paper, we provide a broad survey of the recent
advances in convolutional neural networks. We detailize the improvements of CNN
on different aspects, including layer design, activation function, loss
function, regularization, optimization and fast computation. Besides, we also
introduce various applications of convolutional neural networks in computer
vision, speech and natural language processing.
