Artificial intelligence

Event

Implementing AI in Vision Systems

The focus of this webinar will be the opportunities and challenges of improving the capabilities of imaging systems.

The webinar will have four presentations from experts covering overviews of the opportunity, implementation techniques and case studies.

The event is aimed at both the users of technology, who want to understand the capabilities of technologies, as well as product development engineers, designers and product managers who are looking to improve the capabilities of the systems that they design.

Decoding the dichotomy: Traditional image processing versus deep learning

12 June 2020
This article is brought to you by: 
HCL Technologies

This paper will analyse the benefits and drawbacks of traditional image processing and deep learning. It aims to provide clarity on the subject of deep learning, which can then help data scientists and industries choose the most suitable method depending on the task.

Tags: 
Deep learning
Computer vision
Image processing
Artificial intelligence

Visualisation of the movements of road users in the city of Umeå. Besides counting the tracking over multiple counting lines, Viscando also analysed the tendency for traffic conflict. Credit: Viscando

Feature

Vision algorithms take control of traffic

12 February 2020

Greg Blackman explores the vision and AI technology transforming our roads, as the transport sector gathers for the Intertraffic Amsterdam trade fair

Press release

AI Gateway platform

21 January 2020

Pleora Technologies has introduced an artificial intelligence platform that simplifies the deployment of machine learning capabilities to improve the reliability and lower the cost of visual quality inspection

Press release

IDS NXT Ocean

14 January 2020

IDS NXT Ocean is an all-in-one solution that makes it easy for users to get started with AI-based image processing

Analysis and opinion

Making AI production-ready

3 December 2019

Following speaking at Embedded Vision Europe, Pierre Gutierrez, lead machine learning researcher at Scortex, writes about the challenges of deploying deep learning on the factory floor

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