Welcome to the website of the Center of Excellence for Document Analysis and Recognition (CEDAR). A wide variety of documents are encountered by each of us everyday. They cover all spheres of our lives including commerce, education, law, health, religion, music and entertainment. Some of these documents have a simple and predictable structure such as a page in a printed book. Others have much more complex structure such as those involving figures, tables, logos, signatures, handwriting, etc. Discovering methods and algorithms for analyzing the structure and content of complex documents, and their generalization to related domains, is the focus of research at CEDAR.

Drones are becoming more common in our skies, performing a variety of tasks, from taking photos to monitoring crops and potentially even delivering broadband. But there are strict rules about their usage, which has led some to come up with innovative ways to fly such vehicles more safely. "I'm using a dog leash for a small dog," says roboticist Sergei Lupashin as he demonstrates a new kind of consumer-friendly drone at the Ted (Technology, Entertainment and Design) conference in Vancouver. By tethering it, he hopes the Fotokite, as it is called, can avoid some of the issues faced by unmanned aerial vehicles (UAVs), which are banned without a special licence because of safety and privacy concerns. "It doesn't rely on GPS [ Global Positioning System], sophisticated machine vision, radio, it doesn't even use a compass. Most crashes today happen because of GPS, radio or piloting issues," says Dr Lupashin.

Blog posts can be strange and unpredictable things. There are times when I pour a ton of energy and creativity into a post only to have it largely ignored. Other times I quickly and haphazardly put something together and it ends up attracting thousands of hits. Such was the case with my recent post, Must-know terms for today's intelligentsia. Owing to all the interest, feedback and requests, I've decided to revise the list and provide greater detail and links. I apologize for not providing this in the first place. Before I get into the list, however, I'd like to clarify the purpose of this exercise. First, I am trying to come up with a list of the most fundamental and crucial terms that are coming to define and will soon re-define the human condition, and that subsequently should be known by anyone who thinks of themselves as an intellectual. I admit that there's an elitist and even pompous aspect to this exercise, but the fact of the matter is that the zeitgeist is quickly changing. It's not enough anymore to be able to quote Dostoevsky, Freud and Darwin. This said, while my list of terms is'required' knowledge, I am not suggesting that it is sufficient. My definition of an'intellectual' also requires explanation. To me an intellectual in this context is an expert generalist -- a polymath or jack-of-all-trades who sees and understands the Big Picture both past, present and future.

In the future according to robotics researchers, robots will likely fight our wars, care for our elderly, babysit our children, and serve and entertain us in a wide variety of situations. But as robotic development continues to grow, one subfield of robotics research is lagging behind other areas: roboethics, or ensuring that robot behavior adheres to certain moral standards. In a new paper that provides a broad overview of ethical behavior in robots, researchers emphasize the importance of being proactive rather than reactive in this area. The authors, Ronald Craig Arkin, Regents' Professor and Director of the Mobile Robot Laboratory at the Georgia Institute of Technology in Atlanta, Georgia, along with researchers Patrick Ulam and Alan R. Wagner, have published their overview of moral decision making in autonomous systems in a recent issue of the Proceedings of the IEEE. "Probably at the highest level, the most important message is that people need to start to think and talk about these issues, and some are more pressing than others," Arkin told PhysOrg.com.

It's not a vulture or crow but a Falcon--a new brand of unmanned aerial vehicle, or drone, and Johnson is flying it. The sheriff's office here in Mesa County, a plateau of farms and ranches corralled by bone-hued mountains, is weighing the Falcon's potential for spotting lost hikers and criminals on the lam. A laptop on a table in front of Johnson shows the drone's flickering images of a nearby highway. Standing behind Johnson, watching him watch the Falcon, is its designer, Chris Miser. Rock-jawed, arms crossed, sunglasses pushed atop his shaved head, Miser is a former Air Force captain who worked on military drones before quitting in 2007 to found his own company in Aurora, Colorado. The Falcon has an eight-foot wingspan but weighs just 9.5 pounds.

The arguments against the death penalty in the United States have centered on due process and fairness. Since the death penalty is so rarely rendered and subsequently applied, it appears on the surface to be arbitrary. Considering the potential utility of determining whether or not a death row inmate is actually executed along with the promising behavior of Artificial Neural Networks (ANNs) as classifiers led us into the development, training, and testing of an ANN as a tool for predicting death penalty outcomes. For our ANN we reconstructed the profiles of 1,366 death row inmates by utilizing variables that are independent of the substantive characteristics of the crime for which they have been convicted. The ANN's successful performance in predicting executions has serious implications concerning the fairness of the justice system.

In this paper, we develop a knowledge representation model for the innovative intelligent retrieval of legal cases, which provides effective legal case management. Examples are taken from the domain of accident compensation. A new set of sub-elements for legal case representation (sub-issues, pro-claimant, pro-respondent and contextual features) has been developed to extend the traditional representation elements of issues and factors. In our representation model, an issue may need to be further decomposed into sub-issues; factors are categorised into pro-claimant and pro-respondent factors; and contextual features are also introduced to help retrieval. These extensions can effectively reveal the factual relevance between legal cases.

For three decades, Mr. Phillips had focused on writing software to allow computers to understand human speech. In 2006, he had co-founded a voice recognition company, and eventually executives at Apple, Google and elsewhere proposed partnerships. Mr. Phillips's technology was even integrated into Siri itself before the digital assistant was absorbed into the iPhone. But in 2008, Mr. Phillips's company, Vlingo, had been contacted by a much larger voice recognition firm called Nuance. "I have patents that can prevent you from practicing in this market," Nuance's chief executive, Paul Ricci, told Mr. Phillips, according to executives involved in that conversation. Mr. Ricci issued an ultimatum: Mr. Phillips could sell his firm to Mr. Ricci or be sued for patent infringements. When Mr. Phillips refused to sell, Mr. Ricci's company filed the first of six lawsuits. Soon after, Apple and Google stopped returning phone calls. The company behind Siri switched its partnership from Mr. Phillips to Mr. Ricci's firm. And the millions of dollars Mr. Phillips had set aside for research and development were redirected to lawyers and court fees. When the first lawsuit went to trial last year, Mr. Phillips won.

IT'S EVERYONE'S FONDEST DREAM: A COMPUTER THAT WILL do your legal work and won't bill you at $400 an hour. Sorry, it's not about to happen anytime soon. But then there's Frederic Parnon, a former Manhattan litigator who left his firm five years ago to develop software that can be used to give legal advice of sorts. Working from a cramped, nondescript lab above Rockefeller Center, Parnon has spent more than $1 million of his own moneycreating a program called Jnana, which means "knowledge"in Sanskrit. Already, a handful of companies and law firms, such as General Electric, J.P. Morgan and Davis Polk & Wardwell, have bought the program and customized it for their needs. Typically the program is made available to employees through the Internet, allowing them access to advice they aren't getting–or are paying to get from law firms.

The idea that computers are people has a long and storied history. It goes back to the very origins of computers, and even from before. There's always been a question about whether a program is something alive or not since it intrinsically has some kind of autonomy at the very least, or it wouldn't be a program. There has been a domineering subculture--that's been the most wealthy, prolific, and influential subculture in the technical world--that for a long time has not only promoted the idea that there's an equivalence between algorithms and life, and certain algorithms and people, but a historical determinism that we're inevitably making computers that will be smarter and better than us and will take over from us. You'll have a figure say, "The computers will take over the Earth, but that's a good thing, because people had their chance and now we should give it to the machines."