This code pattern is part of the Getting started with IBM Maximo Visual Inspection learning path. In this code pattern, learn how to deploy a customizable dashboard to visualize video and image analytics. With this customizable dashboard, you can upload images to be processed by IBM Maximo Visual Inspection (using object recognition and image classification), download the analyzed results, and view analytics through interactive graphs. When you have completed this code pattern, you understand how to build a dashboard using Vue.js and IBM Maximo Visual Inspection APIs to generate and visualize image analytics. Find the detailed steps for this pattern in the README file.

India is a breeding ground for many industries. The increase in educated population and the run towards growth has unraveled technology into the country. Today, technology is a core element of growth in the Indian ecosystem. While well-established companies are embracing artificial intelligence for further improvement, Indian start-ups are ballooning like never before. Fortunately, technology-based Indian start-ups landscape has evolved to become the 3rd largest in the world.

Deep learning1 has revolutionized the field of biomedical image analysis. Conventional approaches have used problem-specific algorithms to describe images with manually crafted features, such as cell morphology, count, intensity, and texture. Feature learning with deep convolutional neural networks is implicit, and training the network usually focuses on particular tasks, such as breast cancer detection in mammography2, subcellular protein localization3, or plant disease detection4. Training a deep network usually requires a large number of images, which limits its utility. For example, the classifier for plant disease detection by Mohanty et al.4 was trained on 54,306 images of diseased and healthy plants, and the yeast protein localization model by Kraus et al.3 was inferred from 22,000 annotated images, but not everyone who could benefit from image analysis has so many well-annotated images.

There's a relatively simple formula which describes "weak" or "narrow" artificial intelligence: AI ML TD HITL. To be more specific, this is the definition of supervised machine learning, which is the most common method to produce artificial intelligence. Strong AI – as defined by the Turing test – is when a human has a conversation with a machine and cannot tell it was not a human, based on the way it responds to questions. The optimists believe that strong AI is 10-15 years away whilst the realists/pessimists say not before the end of this century. Over 90% of all human knowledge accumulated since the beginning of time, is unstructured data i.e. text, images, audio and video.

The applications of image analytics are endless. Organizations are starting to realize the possibilities of how to extract value from unstructured data, such as images or video footage, to create a new and enticing customer experience within retail, entertainment, transportation and airport security, insurance claims, and more. Here are five image analytics applications that are unexpected, disruptive, and creative. On June 26th, I'll be talking about image analytics use cases at the Boston Area SAS Users Group in my Image Processing: Seeing the World through the Eyes of SAS Viya talk. Curious to know who attended the Royal Wedding?

In the 2012 Hollywood movie "Act of Valor", US Navy Seals launch a Raven UAV to procure live video streaming for identifying targets prior to a raid. In yet another movie, "Zero Dark Thirty", analysts use FMV/ drone feed to re-create Bin Laden's compound for training US Navy Seals, and later guide them to accomplish their mission. The growing use of image analytics in tracking, detecting, analyzing and predicting outcomes have been effectively used by story writers to piece amazing stories. Image analytics is a technique by which an image is digitally processed for extracting and analyzing data for insightful information. Big data still remains a scary and invincible concept, because of the unmanageable amount of unstructured data present in it.

I am new to the image analytics and processing. Is there any road map for learning this? Is it right to start with computer vision or should i need to know something even before starting with CV? Please suggest.

Business experiments: Business experiments, experimental design and AB testing are all techniques for testing the validity of something – be that a strategic hypothesis, new product packaging or a marketing approach. It is basically about trying something in one part of the organization and then comparing it with another where the changes were not made (used as a control group). It's useful if you have two or more options to decide between. Visual analytics: Data can be analyzed in different ways and the simplest way is to create a visual or graph and look at it to spot patterns. This is an integrated approach that combines data analysis with data visualization and human interaction.

Today, I sent super-hip dress socks to a friend who lives in Chicago while sitting at my sons' swim meet in Indianapolis. Using a mobile app infused with cognitive, I was able to find and order a really cool gift that I otherwise would not have thought of in less than three minutes. I did it using the 1-800-Flowers mobile app with a new AI gift concierge called GWYN. Now I have one less thing on the to-do list. I sent the gift on time, and the best part is that I think he'll really like it.