"Image understanding (IU) is the research area concerned with the design and experimentation of computer systems that integrate explicit models of a visual problem domain with one or more methods for extracting features from images and one or more methods for matching features with models using a control structure. Given a goal, or a reason for looking at a particular scene, these systems produce descriptions of both the images and the world scenes that the images represent."
– Image Understanding, by J.K. Tsotos. In Encyclopedia of Artificial Intelligence. Stuart C. Shapiro, editor. 1987. New York: John Wiley & Sons.
Whether you're interested in learning how to apply facial recognition to video streams, building a complete deep learning pipeline for image classification, or simply want to tinker with your Raspberry Pi and add image recognition to a hobby project, you'll need to learn OpenCV somewhere along the way. The truth is that learning OpenCV used to be quite challenging. The documentation was hard to navigate. The tutorials were hard to follow and incomplete. And even some of the books were a bit tedious to work through. The good news is learning OpenCV isn't as hard as it used to be. And in fact, I'll go as far as to say studying OpenCV has become significantly easier. And to prove it to you (and help you learn OpenCV), I've put together this complete guide to learning the fundamentals of the OpenCV library using the Python programming language. Let's go ahead and get started learning the basics of OpenCV and image processing. By the end of today's blog post, you'll understand the fundamentals of OpenCV.
The OpenPOWER workshop on PowerAI hosted by the NHCE on 19th of December 2017. The Program, led and managed by Ganesan Narayanasamy introduced a wide range of specialist topics ranging from IBM powerAI, deep learning, machine learning, tensorFlow frameworks, Image classification with example. In this session an introduction to OpenPower foundation was delivered.This included an overview of the cooperation of over 300 institutions ranging from academia to industry as well as a more in depth look at some of the success and developments currently underway within the OpenPOWER framework. The Oak Ridge Leadership Computing Facility provides the open scientific community access to America's fastest, most powerful supercomputer and is a key member of the OpenPOWER Founation. Also included an outline of the conventionally used qubit technologies as well as an indication of the current status of the quantum computer projects underway at some of the lead player institutions including IBM, Microsoft and NASA.