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Automatically Measuring Soccer Ball Possession with AI and Video Analytics

Algorithms, Articles, Object Identification, Object Tracking, Software, Tryolabs /

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 […]

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

Algorithms, Articles, Au-Zone Technologies, Face Detection, Industrial Vision (Computer Vision), Object Identification, Object Tracking, Software, Tools /

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

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

Algorithms, Articles, NVIDIA, Processors, Software, Tools /

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

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From DALL·E to Stable Diffusion: How Do Text-to-Image Generation Models Work?

Algorithms, Articles, Software, Tools, Tryolabs /

This article was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. The machine learning community lost its mind when OpenAI released DALL·E in early 2021. Previous years had seen a lot of progress in models that could generate increasingly better (and more realistic) images given a written caption, but

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DNN-Based Object Detectors

Algorithms, Articles, Au-Zone Technologies, Software, Tools /

This article was originally published at Au-Zone Technologies’ website. It is reprinted here with the permission of Au-Zone Technologies. Unlike image classifiers, which simply report on the most important objects within an image, object detectors determine where objects of interest are located, their sizes and class labels within an image. Consequently, object detectors are central

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How We Cleaned Up PASCAL and Improved mAP By 13%

Algorithms, Articles, Hasty, Software, Tools /

This article was originally published at Hasty’s website. It is reprinted here with the permission of Hasty. We cleaned up all 17.120 images of the PASCAL VOC 2012 dataset in a week using Hasty’s AI-powered QC feature. We found that 6.5% of the images in PASCAL had different errors (missing labels, class label errors, etc.).

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How to Build a Custom Embedded Stereo System for Depth Perception

Algorithms, Articles, Processors, Sensors and Cameras, Software, Teledyne Digital Imaging, Tools /

This article was originally published at Teledyne FLIR’s website. It is reprinted here with the permission of Teledyne FLIR. There are various 3D sensor options for developing depth perception systems including, stereo vision with cameras, lidar, and time-of-flight sensors.  Each option has its strengths and weaknesses.  A stereo system is typically low cost, rugged enough

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Transformers in Computer Vision

Algorithms, Articles, Axelera AI, Software, Tools /

This technical article was originally published at Axelera AI’s website. It is reprinted here with the permission of Axelera AI. Convolutional Neural Networks (CNN) have been dominant in Computer Vision applications for over a decade. Today, they are being outperformed and replaced by Vision Transformers (ViT) with a higher learning capacity. The fastest ViTs are

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Multilayer Perceptrons (MLP) in Computer Vision

Algorithms, Articles, Axelera AI, Software, Tools /

This technical article was originally published at Axelera AI’s website. It is reprinted here with the permission of Axelera AI. Convolutional neural networks (CNNs) still dominate today’s computer vision. Recently, however, networks based on transformer blocks have also been applied to typical computer vision tasks such as object classification, detection, and segmentation, attaining state-of-the-art results

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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.

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