The growing field of Deep Learning (DL) has major implications for critical and even life-saving practices, as in medical imaging. Learn about medical imaging and how DL can help with a range...

Doctors have been using medical imaging techniques to diagnose diseases like cancer for many years. However, Artificial Intelligence (AI) has the potential to take this technology further and to improve medical imaging...

With successful experimental results and wide applications, Deep Learning (DL) has the potential to change the future of healthcare. The use of Artificial Intelligence (AI) has become increasingly popular and is now...

A capsule network is a neural network architecture developed by Stanford scientist Geoffrey Hinton. In the capsule network, a distinct approach is applied to image processing, which includes equivariant mapping and the...

Fully connected layers are an essential component of Convolutional Neural Networks (CNNs), which have been proven very successful in recognizing and classifying images for computer vision. The CNN process begins with convolution...

The world around us is full of detail, and we intuitively understand the difference between natural and fake objects. The sheer complexity of an individual voice or face makes it almost unthinkable...

The perceptron is the basic unit powering what is today known as deep learning. It is the artificial neuron that, when put together with many others like it, can solve complex, undefined...

Advances in the field of computer vision have been spearheaded by the adoption of Convolutional Neural Networks (CNNs). There are a number of related architectures available, among them the Region-CNN, used for object...

Convolutional Neural Networks (CNNs) were originally designed for deep learning computer vision tasks, but they have proven highly useful for Natural Language Processing (NLP) tasks as well. A primary use case is sentence...