This blog post was originally published at Tryolabs’ website. It is reprinted here with the permission of Tryolabs. This is the third entry in our Road to Machine Learning series; if you read the first and second entries and did your homework, congratulations! The force is growing on you! By now, you should feel familiar […]
Object Detection and Tracking Step by Step Guide: A Hands-on Exercise Read More +
This blog post was originally published at Visidon’s website. It is reprinted here with the permission of Visidon. In the realm of computer vision, object detection plays a vital role in various applications, including surveillance systems, autonomous driving, and image recognition. However, accurate object detection can be challenging in real-world scenarios due to the presence
Enhancing Object Detection: The Impact of Visidon CNN-based Noise Reduction Read More +
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. LED flicker can impact the performance of embedded vision systems. To address this, LED Flicker Mitigation (LFM) is crucial for applications like AMRs, ADAS, fleet management systems, etc. In this blog post, you’ll learn more
What is LED Flicker Mitigation and Why is It a Critical Camera Feature? Read More +
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. On-device AI processing offers must-have benefits for privacy, performance, personalization, cost, and energy In the mid-’90s, the World Wide Web ushered in the era of massive remote data center computing now known as the cloud. And this
5 Benefits of On-device Generative AI Read More +
This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. We did the math: And here’s the cost of today’s AI Big Bang As indicated in our whitepaper, The Future of AI is Hybrid (part 1): Unlocking the generative AI future with on-device and hybrid AI, a
Generative AI Trends by the Numbers: Costs, Resources, Parameters and More Read More +
This blog post was originally published at Arm’s website. It is reprinted here with the permission of Arm. The integration of ML into IoT is sparking exponential growth and shaping a dynamic ecosystem The pace of Internet of Things (IoT) innovation has quickened in recent years, but it’s now being kicked into hyper drive. The
Machine Learning Transforms the Internet of Things Read More +
This blog post was originally published at Tenyks’ website. It is reprinted here with the permission of Tenyks. We break down and demystify common object detection metrics, including mean average precision (mAP) and mean average recall (mAR). This is Part 1 of our Tenyks Series on Object Detection Metrics. This post provides insights into how
Mean Average Precision (mAP): Common Definition, Myths and Misconceptions Read More +
This blog post was originally published at e-con Systems’ website. It is reprinted here with the permission of e-con Systems. Let’s explore the advantages and disadvantages of manual and automated microscopy and examine how AI-based embedded vision technologies are changing the medical and life science industry. Microscopy has long been an essential tool in various
Manual Microscopes vs. AI-based Automated Digital Microscopes: An In-depth Look Read More +
This blog post was originally published at Expedera’s website. It is reprinted here with the permission of Expedera. Despite significant improvements in throughput, edge AI accelerators (Neural Processing Units, or NPUs) are still often underutilized. Inefficient management of weights and activations leads to fewer available cores utilized for multiply-accumulate (MAC) operations. Edge AI applications frequently
A Packet-based Architecture For Edge AI Inference Read More +
This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Vision Transformers (ViTs) are taking computer vision by storm, offering incredible accuracy, robust solutions for challenging real-world scenarios, and improved generalizability. The algorithms are playing a pivotal role in boosting computer vision applications and NVIDIA is making
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