Our second example deals with a more challenging problem: the recognition of hand-printed letters of the alphabet. The characters that people print in the ordinary course of filling out forms and questionnaires are surprisingly varied. Gaps abound wherecontinuous lines might be expected; curves and sharp angles appear interchangeably; there is almost every imaginable distortion of slant, shape and size. Even human readers cannot always identify such characters; their error rate is about 3 per cent on randomly selected letters and numbers, seen out of context.
– from Oliver G. Selfridge & Ulric Neisser. PATTERN RECOGNITION BY MACHINE . In Computers & thought, Edward A. Feigenbaum and Julian Feldman (Eds.). MIT Press, Cambridge, MA, USA, 1963. pp. 8-30.
Money is one of many challenges for people who are visually impaired. Its features include recognizing different kinds of products which are then spoken into an earpiece. "Oreos cookies, it will tell me it's Oreos cookies this is how you recognize the product," said Pedro. Dr. Georgia Crozier with the Moore Eye Institute says MyEye is unlike other devices that work with magnification. This sees for the person and translates it into words.
E-readers have become one of the most pervasive pieces of tech for many reasons. They survive alongside tablets because they're accessible -- Amazon's entry-level Kindle is just $80 -- and don't require daily charging. E-ink displays don't strain your eyes nearly as much as backlit screens, nor do they keep you up at night. Above all else, though, they can hold the entire works of Shakespeare countless times over while being thinner and lighter than any paperback. But this idea of portability, of condensing the written word into a format only a device can understand, is older than The Great Gatsby.
Ray Kurzweil's impact on my life in general but especially on what I have been doing for the past 3 or 4 years is hard to exaggerate. It is a simple fact that, if I haven't read his seminal book The Singularity is Near, I would be neither blogging nor podcasting about exponential technologies, not to mention going to Singularity University. And so it was with great excitement and some trepidation that I went to interview Dr. Kurzweil in his office in Boston. Part of my trepidation came from some technical concerns: I wish I could buy a better camera. I wish I could hire a team of audio and video professionals so that I can focus on the interview itself.
With each delivery cycle, measure the results, see the impact of AI, and use that to raise awareness with the C-Suite on how AI can transform operations. Many packaged cognitive services, such as optical character recognition, sentiment analysis, or speech to text, are very easy to implement. However, to leverage these appropriately, one must understand how each solution can fit within overall business processes and where it must be applied to accelerate intelligent automation. Beyond plug-and-play cognitive services, organizations can start to explore custom machine learning algorithms to create unique predictive models based on their business data. Accessing the technology to enable this is straightforward, but understanding an organization's unique data and process requirements to apply machine learning to maximum impact remains the biggest challenge.
Whether you're aware of it or not, artificial intelligence (AI) has a ubiquitous presence in our lives today – think the personalised playlists on Spotify or the'Recommended for you' lists on Netflix, both of which use AI to curate a selection tailored just for you. Now its presence is being felt in the area of document management, with AI and cognitive computing set to revolutionise the ways in which we store, archive, process and extract information. Here are 5 ways AI is transforming document management systems . Automatic classification and processing - While OCR (optical character recognition) technology allows for text recognition, AI takes this a step further by being able to "read" the information on that document, classify it correctly and automate workflows based on that classification – all at a fraction of the speed a human could. While the system is initially guided by a set of rules, its identification and processing capabilities continue to improve using machine learning, meaning it is able to learn from repeated exposure to documents, as well as from the actions taken by employees upon those documents.
This video course is a practical guide for developers who want to get started with building computer vision applications using Python 3. The video is divided into six sections: Throughout this video course, three image processing libraries: Pillow, Scikit-Image, and OpenCV are used to implement different computer vision algorithms. The course will help you build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we look at in the course are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet. Saurabh Kapur is a computer science student at Indraprastha Institute of Information Technology, Delhi. His interests are in computer vision, numerical analysis, and algorithm design.
Not even the highest Roman Catholic church archivists know what's hiding in the archives' endless volumes, which are carefully stored near the Sistine Chapel. Only a tiny amount of these archives have been digitized–the rest is an endless ocean of inaccessible papers and parchments. Going through its tomes in search of something would be a task that not even the goddess Minerva herself would be able to accomplish. Some libraries have used technology to digitize their collections, like Optical Character Recognition software that's trained to recognize fixed, separated individual letter shapes. However, OCR is useless when it comes to the endless variety of free-flowing cursive styles featured in many of the Vatican's tomes, which go all the way back to the eighth century.
Somewhere within the Vatican exists the Vatican Secret Archives, whose 53 miles of shelving contains more than 600 collections of account books, official acts, papal correspondence, and other historical documents. Though its holdings date back to the eighth century, it has in the past few weeks come to worldwide attention. This has brought about all manner of jokes about the plot of Dan Brown's next novel, but also important news about the technology of manuscript digitization. It seems a project to get the contents of the Vatican Secret Archives digitized and online has made great progress cracking a problem that once seemed impossibly difficult: turning handwriting into computer-searchable text. In Codice Ratio is "developing a full-fledged system to automatically transcribe the contents of the manuscripts" that uses not the standard method of optical character recognition (OCR), which looks for the spaces between words, but a new way that can handle connected cursive and calligraphic letters.