Convolutional neural networks (CNNs) are a class of deep neural networks commonly used in computer vision tasks such as image and video recognition, object detection and image segmentation.

The bad news is that neural network models are considerably larger than typical photographic images, offering attackers the ability to hide far more illicit data inside them without detection.

Adam Harley’s 3D Visualization of a Convolutional Neural Network lets you look inside the inner workings of artificial intelligence. Screenshot/ Adam Harley ...

The "Hello World" of image classification is a convolutional neural network (CNN) applied to the MNIST digits dataset. A good way to see where this article is headed is to take a look at the ...

This paper proposes an end-to-end trained fully convolutional neural network model to process 3D image volumes. Unlike previous works that processed the input volumes slice-wise or patch-wise, the ...

Convolutional Neural Networks (CNN) are mainly used for image recognition. The fact that the input is assumed to be an image enables an architecture to be created such that certain properties can be ...

The complexity of convolutional neural networks (CNN), the deep learning architecture commonly used in computer vision tasks, is usually measured in the number of parameters they have. The more ...

They used a convolutional neural network (CNN), a type of machine learning algorithm particularly well suited to image recognition and trained it on more than 600 images of chromosomes which had ...