Perceptron A perceptron is a binary classification algorithm modeled after the functioning of the human brain—it was intended to emulate the neuron. The perceptron, while it has a simple structure, has the...

What are Artificial Neural Networks and Deep Neural Networks? Artificial Neural Networks (ANN) is a supervised learning system built of a large number of simple elements, called neurons or perceptrons. Each neuron...

As the field of computer vision grows, increasingly efficient tools are being built to more finely parse visual information. Deep learning for computer vision and Convolutional Neural Networks (CNNs) are the primary technologies being...

Advances in AI and deep learning have enabled the rapid evolution in the fields of computer vision and image analysis. This is all made possible by the emergence and progress of Convolutional...

As we strive to create machines that can handle complex tasks, deep learning is increasingly coming into the spotlight. Because many of the tasks we want our machines to perform are intuitive...

Creating a Deep Learning (DL) model involves training Artificial Neural Networks (ANN) to perform various tasks. This process usually includes exposing the model to thousands or millions of datasets. This type of...

Deep reinforcement learning is a promising combination between two artificial intelligence techniques: reinforcement learning, which uses sequential trial and error to learn the best action to take in every situation, and deep...

Object detection algorithms enable many advanced technologies and are a primary research focus for many industries from transportation to healthcare. For example, a common use for object detection algorithms is to implement...

Object tracking is a field within computer vision that involves tracking objects as they move across several video frames. In this article, we’ll address the difference between object tracking and object detection,...