This article was originally published at Intel’s website. It is reprinted here with the permission of Intel. The Deep Learning Deployment Toolkit from Intel helps deliver optimized inferencing on Intel® architecture, helping bring the power of AI to clinical diagnostic scanning and other healthcare workflows Executive Summary Deep learning and other forms of artificial intelligence […]
This article was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. DeepStream SDK 3.0 is about seeing beyond pixels. DeepStream exists to make it easier for you to go from raw video data to metadata that can be analyzed for actionable insights. Calibration is a key step in this
Using Calibration to Translate Video Data to the Real World Read More +
This article was originally published at NVIDIA's website. It is reprinted here with the permission of NVIDIA. As we design deep learning networks, how can we quickly prototype the complete algorithm—including pre- and postprocessing logic around deep neural networks (DNNs) —to get a sense of timing and performance on standalone GPUs? This question comes up
Using MATLAB and TensorRT on NVIDIA GPUs Read More +
This article was originally published at Basler's website. It is reprinted here with the permission of Basler. If I can't read the writing on a piece of paper, there's usually a simple solution: I hold the text under a lamp. If I want to see faint contours on the paper, I hold the sheet up
Lighting in Image Processing Read More +
Augmented reality (AR) and related technologies and products are becoming increasingly popular and prevalent, led by their adoption in smartphones, tablets and other mobile computing and communications devices. While developers of more deeply embedded platforms are also motivated to incorporate AR capabilities in their products, the comparative scarcity of processing, memory, storage, and networking resources
Computer Vision for Augmented Reality in Embedded Designs Read More +
Key to the widespread adoption of embedded vision is the ease of developing software that runs efficiently on a diversity of hardware platforms, with high performance, low power consumption and cost-effective system resource needs. In the past, this combination of objectives has been a tall order, since it has historically required significant code optimization for
OpenVX Implementations Deliver Robust Computer Vision Applications Read More +
Key to the widespread adoption of embedded vision is the ease of developing software that runs efficiently on a diversity of hardware platforms, with high performance, low power consumption and cost-effective system resource needs. In the past, this combination of objectives has been a tall order, since it has historically required significant code optimization for
This article was originally published at Basler's website. It is reprinted here with the permission of Basler. What is unique about NIR Cameras? “Near-infrared” (NIR) is the portion of the electromagnetic spectrum directly adjacent to the visible range; therefore it cannot be perceived with the human eye. NIR-optimized industrial cameras are popular for applications that
NIR: Seeing Clearly Even in Low Light Read More +
This article was originally published at Texas Instruments' website. It is reprinted here with the permission of Texas Instruments. The robustness and reliability of a self-driving car’s computer vision system has received a lot of news coverage. As a vision software engineer at TI helping customers implement advanced driver assistance systems (ADAS) on our TDAx
Tips For Designing a Robust Computer Vision System For Self-driving Cars Read More +
This article was originally published at Basler's website. It is reprinted here with the permission of Basler. For many machine vision applications, image data must be acquired, transmitted and evaluated within a set timeframe. This is known as “real-time capability”. This term can apply to a system, its components, and the software that communicates between
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