In this article we are going to look at embedding entire sentences, rather than individual words, so that we can get much more accurate results in detecting emotion from the text.
In this article series, we'll look at how to use AI and deep learning on video frames to ensure people are maintaining adequate social distancing in crowds.
In this we discuss improvements we can make to the software in terms of performance or accuracy. We also compare our homebrew open-source system to commercial vehicle speed detection systems.
In this series of articles we will use a deep neural network (DNN) to perform coin recognition. Specifically, we will train a DNN to recognize the coins in an image.
In this article, we’ll test our detection algorithm on a Raspberry Pi 3 device and create the "scare pests away" part of our pest eliminator by playing a loud sound.
The Intel® Distribution of OpenVINO™ toolkit is a comprehensive toolkit for quickly developing applications and solutions that solve a variety of tasks including emulation of human vision, automatic speech recognition, natural language processing, recommendation systems, and many others.
In this article we take you through the process of migrating your existing deep learning models over to Gaudi and show the basic steps to get your model ready to run.
In this article, we focus on developing a computer vision framework that can run the various Machine Learning and neural network models – like SSD MobileNet – on live and recorded vehicle traffic videos.
In this article, we explore the different ways of measuring vehicle speed and the different Deep Learning models for object detection that can be used in our TrafficCV program.
In this article, we set up a development environment on Windows 10 for cross-platform computer vision and machine learning projects to run on our Pi device.
In this article, we have a look at the details of the TrafficCV implementation and the various object detection models to use for detecting vehicles and calculating their speed.
This article series will show you how to build a reasonably accurate traffic speed detector using nothing but Deep Learning, and run it on an edge device like a Raspberry Pi.