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Face Tracking in Python using Xailient Face Detector and Dlib

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Face tracking is detecting a set of faces in frame 1 of a video, establishing a correspondence between the frames, and maintaining a unique ID for each of the faces throughout the video. It is being used …

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Xailient Announces Face Recognition AI for Sony’s Intelligent Vision Sensor IMX500 with Impressive 97.8% Accuracy Up to 3 Meters

SYDNEY, Nov. 29, 2021 /PRNewswire/ — Xailient announced the world’s most power-efficient Face Recognition AI, which runs on the IMX500, the world’s first intelligent vision sensor with edge AI processing capability from Sony Semiconductor Solutions Corporation (“Sony”). Xailient’s Face Recognition enables high-speed edge AI processing with low-power consumption using Sony’s IMX500 – a chip so …

Xailient Announces Face Recognition AI for Sony’s Intelligent Vision Sensor IMX500 with Impressive 97.8% Accuracy Up to 3 Meters Read More +

Face Detection with 7 Lines of Code in Python

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Only a few years ago, if someone asked me to work on a project that required detecting a person’s face using the camera, to be honest, I would have shut down my laptop and run as far …

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Real-time Face Detection on Raspberry Pi

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. A step-by-step guide to implement real-time face detection on a Raspberry Pi running 24 frames per second. In this post, I will guide you through a step-by-step process of implementing real-time face detection on a Raspberry Pi, running …

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“Introduction to DNN Model Compression Techniques,” a Presentation from Xailient

Sabina Pokhrel, Customer Success AI Engineer at Xailient, presents the “Introduction to DNN Model Compression Techniques” tutorial at the May 2021 Embedded Vision Summit. Embedding real-time large-scale deep learning vision applications at the edge is challenging due to their huge computational, memory, and bandwidth requirements. System architects can mitigate these… “Introduction to DNN Model Compression …

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Integrate Face Detection in Your Application

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Don’t be overwhelmed, because adding face detection to your applications has never been so easy! A lot of the times, face detection is not the primary focus of the application but is an important component and many …

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Maxim Integrated Teams with Xailient to Provide World’s Fastest and Lowest-Power IoT Face Detection

MAX78000 AI microcontroller and Xailient’s Detectum neural network detects and localizes faces in video and images at just 12ms per inference SAN JOSE, Calif., July 27, 2021 /PRNewswire/ — Maxim Integrated Products, Inc. (NASDAQ: MXIM) and Xailient Inc., a company focused on artificial intelligence (AI) for the edge, today announced that Maxim Integrated’s MAX78000 ultra-low …

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You Need to Move from Cloud Computing to Edge Computing Now!

Paper cut cloud looking at the clouds (Image by rawpixel from Pixabay) This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Edge Computing market size is expected to reach USD 29 billion by 2025. In this decade there has been a transformational movement from on-premise Computing …

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Challenges of Running Deep Learning Computer Vision on Computationally Limited Devices

Clear vision using glasses (Photo by timJ on Unsplash) This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Autonomous driving, facial recognition, traffic surveillance, person tracking, and object counting, all of these applications have one thing in common, Computer Vision (CV). Since the success of deep …

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Struggles of Running Object Detection on a Raspberry Pi

Frustrated man (Image by Gerd Altmann from Pixabay) This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Have you ever been so excited after reading a how-to tutorial or a github readme file, only to discover after following it through that it is not really as …

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