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.

Dr. James McCaffrey of Microsoft Research details the 'Hello World' of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset.

A visualization of a convolutional neural network reading an image to determine a number. Screenshot/ Adam Harley ...

AttendSeg is a new neural network architecture from DarwinAI designed to perform image segmentation on low-power/capacity computing devices.

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.

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 ...

Research shows that CNNs trained on camouflage detection improve brain tumor classification in MRI scans, highlighting the potential of unconventional training.