How Deep Learning Is Supporting Computer Vision

07/27/2022 | AI, Featured Content, Technology Education

Computer vision sounds like something from the future, but it’s actually being used in almost every industry, from automotive to retail. What is it? Computer vision attempts to emulate the power of the human eye at scale, analyzing thousands or even millions of images to identify and learn from patterns in the data.

You may wonder how analyzing images helps businesses. Computer vision has laid the foundation for advancements in self-driving cars, medical image analysis, and facial recognition — enabling organizations to leverage AI to extract meaningful data from visual input.

The Role of Deep Learning in Computer Vision

To understand how deep learning enhances computer vision, we must go back a few years in the history of machine learning. Previously, for a computer to recognize images, it was necessary to create a database of images. These images then needed to be annotated with specific data to help an application compare and make sense of the visual input.

Machine learning improved this manual process by allowing programmers to code features or tiny applications that could detect patterns in images. These applications could then use a learning algorithm to classify images and detect objects. Even so, machine learning still relies on structured, labeled data, albeit not to the extent that previous manual processes required. It could even use unstructured data after some pre-processing to structure the data.

Deep learning takes this automation a step further by allowing machine learning to eliminate the need for pre-processing. It can take unstructured data and automate feature extraction, allowing algorithms to learn from data with minimal intervention from specialists. How does this benefit people leveraging deep learning computer vision applications?

  • General purpose solution. Machine learning algorithms typically need to be developed specifically for the project they’ll be used on. But deep learning allows you to create models that can be reused for different applications.
  • Limited need for instruction. When using a deep learning algorithm, the team only needs to develop or choose the algorithm they’ll be using and feed it the necessary visual data. With enough examples, the neural network can identify images without additional instruction.
  • Faster deployment speed. Computer vision is already much faster than humans, but deep learning accelerates it by reducing the need for human input. Since models can work with unstructured data and neural networks are more general purpose, deployment is greatly accelerated.

As deep learning algorithms become more intelligent, the possibilities of computer vision will increase. However, to power deep learning, you need robust computing infrastructure.

Leverage Hardware That Powers Computer Vision

Designing powerful machine learning infrastructure helps set the foundation for deep learning and computer vision. But deploying your hardware takes work. You must analyze your computing requirements, tailor hardware solutions to those needs, and deploy them within your organization, factoring in supply chain and logistics concerns.

Equus Compute Solutions helps its partners by offering an end-to-end machine learning infrastructure solution. We help you through each stage of the process and leverage our partnerships to ensure you get the best value and highest-performing hardware. If you’d like to explore the deep learning infrastructure solutions available, send us a note.


Share This:

Related Posts


Navigating Cybersecurity: What is the Zero Trust Approach?

Cyberattacks are too common to just play defense. Learn how Zero Trust security can help you proactively protect your network...
Read More
Data Management Infrastructure

Storage Solutions for Massive Data Sets: The Backbone of Tomorrow’s AI

High-capacity and low-latency storage is key to managing the never-ending growth in data. Learn how different storage solutions are tailor-made...
Read More
Technology Education Featured Content

The Future of ESG as a Service

Climate disclosure reporting will mean significant changes for business. Learn how proactive companies can claim their strategic advantage during this...
Read More
Press Room Featured Content

Equus Compute Solutions Announces Strategic Partnership with Zscaler

By leveraging Zscaler’s industry leading Zero Trust Exchange™ platform, Equus Compute Solutions can provide its customers with seamless, secure access...
Read More
Data Management Featured Content Technology Education

Immersion and Liquid Cooling in Data Centers: A Dive into Efficiency and Innovation

High-performance computing requires heat dissipation methods that are efficient and cost-effective. Learn how immersion and liquid cooling promote data center...
Read More
AI Featured Content Infrastructure

Secure AI Training: When On-Premise Beats the Cloud

AI model training requires immense amounts of data. Learn how on-premise infrastructure gives you control over data privacy and improves...
Read More
Servers Featured Content Infrastructure Technology Education

Unleashing the Potential: The Benefits of Upgrading from SQL Server 2012

SQL Server 2012 is coming to an end. Learn how upgrading to SQL Server 2022 could benefit your business aside...
Read More
Infrastructure Featured Content Hardware

Why is Zero Trust security key to unlocking the modern workplace?

The modern workplace has accelerated the need for an updated approach to security. Learn how Zero Trust security is helping...
Read More
Featured Content Storage

Solidigm and Equus Compute Solutions Partner to Showcase the Latest in Storage Solutions

New technologies like AI and machine learning, as well as expanding 5G infrastructure, are driving an exponential increase in data...
Read More