convolutional neural networks

April 2, 2021

Applying Convolutional Networks for Better Video Streaming Performance

In the wake of COVID, video streaming is no longer a fun diversion. Organizations are depending on it to keep their workforce moving... and parents are counting on it to keep their kids from going into all-out rebellion mode during lockdowns. We’re all familiar with the hiccups we experience using streaming platforms, so the application of Deep Learning to video encoding and streaming promises to be an interesting frontier.

Convolutional Neural Networks (CNNs) are a form of Deep Learning – machine learning designed to mimic the human brain by creating multiple layers of ‘neuron’ connections based on weighted probabilities – that is commonly used in image recognition. Each neuron represents a combination of features from a dataset, which are activated for prediction through sigmoid, threshold and rectifier functions.

May 10, 2019

Approaching the Problem of Equivariance With Hinton’s Capsule Networks

In this article, we'll look at the problem of equivalence with Hinton's Capsule Networks.

Have a look at this:

January 30, 2019

Medical AI Systems Struggle to Perform Well Across IT Systems

The level of expectation surrounding AI in healthcare has reached fever pitch in recent years, with a number of pilot projects achieving positive early results. Most of these projects involved AI systems being trained on a sample dataset of medical data, such as x-rays or other medical imagery, after which the system was capable of providing early detection of various conditions.

The challenge for many of these systems is that they were usually trained on data from a single healthcare provider, with a common health IT system. A recent study highlights how when faced with data from different health systems, such AI technologies often perform much worse than doctors.

January 28, 2019

Computer Vision Systems Applied to Real Business Problems

Computer Vision has finally found its way out of the lab into real-world applications.

The latest state-of-the-art CV systems, which rely heavily on Deep Learning and Convolutional Neural Networks, are now capable of providing high levels of accuracy in object classification, object detection, and other visual recognition tasks. Companies across various industries are finding multiple use-cases for this groundbreaking tech.