---OVERVIEW---
In this video, I explain step-by-step how Augmented Reality works.

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00:00 - Introduction
00:32 - Defining Augmented Reality
01:00 - Mapping the Surrounding Environment
02:00 - Tracking / Localization Within the Environment…

#9 best model for Image Classification on iNaturalist (Top 1 Accuracy metric)

In this tutorial, you will learn how to compare two images for similarity (and whether or not they belong to the same or different classes) using siamese networks and the Keras/TensorFlow deep learning libraries.

This example shows how to detect the QRS complex of an electrocardiogram (ECG) signal in real time.

Learn how Beril Sirmacek of University of Twente is using MATLAB to develop handheld devices that give patients the opportunity to observe the developments of their skin burns, cancer tissues, or diabetic wounds.

Various pre-trained deep-learning models for the segmentation of biomedical images have been made available to users with little to no knowledge in machine learning. However, testing these tools individually is tedious and success is uncertain.

Here, we…

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

Professor Emma Brunskill, Stanford University
https://stanford.io/3eJW8yT

Professor Emma Brunskill
Assistant Professor, Computer…

Cervical cancer is the fourth most prevalent disease in women. Accurate and timely cancer detection can save lives. Automatic and reliable cervical cancer detection methods can be devised through the accurate segmentation and classification of Pap smear cell…

Levity automatically classifies incoming emails and attachments based on your custom categories so you can sort, route and prioritize without manual tagging.

- Presentation of the problem of image processing in a typical AV/ADAS scenario, both in terms of required resources and of compute paradigm.- Exploring the ...

Implemented in 4 code libraries.

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network - awni/ecg

This tutorial will teach you how to build a people counter using OpenCV, Python, and object tracking algorithms. Using the OpenCV library we'll count the number of people moving "in" and "out" of a store.

In this video we will learn how to modify and manipulate images using the Python Pillow Library. Pillow is a fork of the Python Imaging Library (PIL). It will allow us to do many different things to our images such as: changing their file extension, resizing…

The package managers "pip" and "conda" allow users to install, update, or uninstall Python modules from a command line or directly from a Python noscript.

Both Python and MicroPython are powerhouse programming languages. Each of them is capable of supporting your programming needs to almost the limits of your imagination. Both languages are transportable, open-source, growing in popularity, comparatively easy…

In this tutorial, you will learn how to automatically detect COVID-19 in a hand-created X-ray image dataset using Keras, TensorFlow, and Deep Learning. Like most people in the world right now, I’m genuinely concerned about COVID-19. I find myself constantly…

Learn how to use OpenCV and Deep Learning to detect vehicles in video streams, track them, and apply speed estimation to detect the MPH/KPH of the moving vehicle.