fbpx

Articles

Quantization of Convolutional Neural Networks: Model Quantization

See “From Theory to Practice: Quantizing Convolutional Neural Networks for Practical Deployment” for the previous article in this series. Significant progress in Convolutional Neural Networks (CNNs) has focused on enhancing model complexity while managing computational demands. Key advancements include efficient architectures like MobileNet1, SqueezeNet2, ShuffleNet3, and DenseNet4, which prioritize compute and memory efficiency. Further innovations […]

Quantization of Convolutional Neural Networks: Model Quantization Read More +

From Theory to Practice: Quantizing Convolutional Neural Networks for Practical Deployment

In this dynamic technology landscape, the fusion of artificial intelligence and edge computing is revolutionizing real-time data processing. Embedded vision and edge AI take center stage, offering unparalleled potential for precision and efficiency at the edge. However, the challenge lies in executing vision tasks on resource-limited edge devices. Model compression techniques, notably quantization, emerge as

From Theory to Practice: Quantizing Convolutional Neural Networks for Practical Deployment Read More +

The Foundation Models Reshaping Computer Vision

This article was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. Learn about the Foundation Models — for object classification, object detection, and segmentation —  that are redefining Computer Vision. ‍Foundation models have come to computer vision! Initially limited to language tasks, foundation models can now serve as the backbone of computer

The Foundation Models Reshaping Computer Vision Read More +

NVIDIA TAO Toolkit “Zero to Hero”: A Simple Guide for Model Comparison in Object Detection

This article was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. In Part 2 of our NVIDIA TAO Toolkit series, we describe & address the common challenges of model deployment, in particular edge deployment. We explore practical solutions to these challenges, especially on the issues surrounding model comparison. ‍Here

NVIDIA TAO Toolkit “Zero to Hero”: A Simple Guide for Model Comparison in Object Detection Read More +

A Guide to Optimizing Transformer-based Models for Faster Inference

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. Have you ever suffered from high inference time when working with Transformers? In this blog post, we will show you how to optimize and deploy your model to improve speed up to x10! If you have been keeping

A Guide to Optimizing Transformer-based Models for Faster Inference Read More +

NVIDIA TAO Toolkit “Zero to Hero”: Setup Tips and Tricks

This article was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. A quick setup guide for an NVIDIA TAO Toolkit (v3 & v4) object detection pipeline for edge computing, including tips & tricks and common pitfalls. ‍This article will help you setup an NVIDIA TAO Toolkit (v3 & v4)

NVIDIA TAO Toolkit “Zero to Hero”: Setup Tips and Tricks Read More +

The Guide to Fine-tuning Stable Diffusion with Your Own Images

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. Have you ever wished you were able to try out a new hairstyle before finally committing to it? How about fulfilling your childhood dream of being a superhero? Maybe having your own digital Funko Pop to use as

The Guide to Fine-tuning Stable Diffusion with Your Own Images Read More +

Automatically Measuring Soccer Ball Possession with AI and Video Analytics

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. The World Cup is just around the corner and in Tryolabs everybody is excited to have their national team compete. As the teams prepare for the event, they more than ever rely on AI-assisted sports analytics for inspecting

Automatically Measuring Soccer Ball Possession with AI and Video Analytics Read More +

Monitoring Protection Gear in Hazardous Working Spaces Using DeepView ModelPack & VisionPack

This article was originally published at Au-Zone Technologies’ website. It is reprinted here with the permission of Au-Zone Technologies. Working in a hazardous environment always requires protection to prevent injuries. In most fatal accidents the workers are not wearing the right protection or using it properly. Due to the dynamic nature of some work, danger

Monitoring Protection Gear in Hazardous Working Spaces Using DeepView ModelPack & VisionPack Read More +

Access the Latest in Vision AI Model Development Workflows with NVIDIA TAO Toolkit 5.0

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. NVIDIA TAO Toolkit provides a low-code AI framework to accelerate vision AI model development suitable for all skill levels, from novice beginners to expert data scientists. With NVIDIA TAO (Train, Adapt, Optimize) Toolkit, developers can use the power

Access the Latest in Vision AI Model Development Workflows with NVIDIA TAO Toolkit 5.0 Read More +

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.

Contact

Address

1646 N. California Blvd.,
Suite 360
Walnut Creek, CA 94596 USA

Phone
Phone: +1 (925) 954-1411
Scroll to Top