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Building a Security System using Computer Vision

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Computer Vision. Does it sound familiar?   No?  I am sure the following pictures should look familiar. or this? or this? All of the above, are few out of many applications of Computer Vision technology.  Computer Vision is a field focused on equipping computers, to derive information from the digital images and videos. In short, it has the power to convert a camera lens into an eye.  When a Tesla car runs in autopilot mode, it automatically gains understanding of most of the things on the road, including road path, vehicles, people, traffic sign boards, traffic lights etc. This happens in just the same way, a human driver driving a car understands what his eyes are watching.  Actually it is a number of cameras(similar to human eye) viewing the surroundings, then communicating with the processing system(similar to human brain) in Tesla car, which understands what it is viewing and then takes the required action.  This programmatic communication and the resultant action, is what Computer

Fraud Detection - Using Graph Database

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In Gartner Data and Analytics Summit Feb 2019, Gartner predicted the application of Graph technology to grow by 100% through 2022. The details are available  here  . In addition to social networks and recommendation systems, fraud detection is a field where the value of graph technology cannot be understated.  Today we'll learn the use of Graph technology with a real world business use case of fraud detection.  If you are new to Graph technology, and haven't read my previous publication Graph technology in plain english , I highly recommend to read that once. It will help you to understand the fundamentals of Graph technology and serve as a catalyst for your learning process.  Fraud detection According to the research published by Crowe in July 2019, global fraud losses equate to shocking US$5.127 trillion each year . Fraudsters commit monetary frauds almost every day.  What if such fraud can be detected at an early stage, through prior experience of  some common fraud patt