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Xailient

www.xailient.com

Xailient delivers the world’s fastest, most efficient visual AI, allowing computers to see the way humans do, detecting objects and events from images or videos. We have commercialized university research breakthroughs in neuroscience and computer vision (CV). Inspired by nature, our novel CV techniques are 10 to 100x more efficient than today’s “state of the art”. The result is faster, more accurate and dramatically lower cost CV. Xailient is a pure software provider that is hardware-agnostic, perfect for retail analytics, VMS, inventory management, theft prevention and key COVID use cases e.g. temperature monitoring and people counting. In practice, our Detectum can go beyond a 76x speed improvement and approach 100% cost reduction, by skipping the transmission and computation costs of empty images, for example. Focusing only on what matters (seeing the way humans do), across the field of view and across time, customers eliminate waste and optimize accuracy, cost and speed.

Recent Content by Company

Exploring Data Labeling and the 6 Different Types of Image Annotation

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Data labeling is an essential step in a supervised machine learning task. The same is true for image annotation. Data labeling and image annotations must work together to paint a complete picture. If you show a child …

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Custom Detection Model Training

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. In this post, we will look at the best methods for collecting a training dataset to train a custom detection model. Use of deep learning in computer vision has increased in the last decade. In the past …

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Overcome These 6 Problems with Object Detection

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. There are a number of common problems with object detection. For example, can your object detector detect people and horses in the following image? People on horses (Photo by Paul Chambers on Unsplash) What if the same …

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How to Set Up Raspberry Pi for Computer Vision

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. In this post, I will show you how to set up a Raspberry Pi for computer vision. The Raspberry Pi is a series of low-cost, single-board computers, that are as small as your credit card. They have …

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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 demands by modifying deep-neural networks …

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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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Model Compression: Needs and Importance

Smart City connected by IoT (Image by Tumisu from Pixabay) This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Whether you’re new to computer vision or an expert, you’ve probably heard about AlexNet winning the ImageNet challenge in 2012. That was the turning point in computer …

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The Battlefield of Cutting Edge Face Detectors

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. Face detector is one of the most commonly used AI component today. Whether you are building a system to count the number of people in a room or a home security system that unlocks the door when …

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Real-Time Vehicle Detection with MobileNet SSD and Xailient

This blog post was originally published at Xailient’s website. It is reprinted here with the permission of Xailient. From vehicle counting and smart parking systems to Autonomous Driving Assistant Systems, the demand for detecting cars, buses, and motorbikes is increasing and soon will be as common of an application as face detection. And of course, …

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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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