Research Paper In Computer Science

This paper was new to me, although I’m sure it’s not new to many of you.This paper describes how to identify objects in a video stream without regard to how near or far away they are or how they’re oriented with respect to the camera.

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The top graph summarizes the overall results of the analysis.

This graph shows the Top 10 papers among those who have listed computer science as their discipline .

I would expect that the largest share of readers have it in their library mostly out of curiosity rather than direct relevance to their research.

It’s a fascinating piece of history related to something that has now become part of our every day lives.

Presumably, those interested in popular topics such as machine learning list themselves under AI, which explains the strength of this subdiscipline, whereas papers like the Mapreduce one or the Google paper appeal to a broad range of subdisciplines, giving those papers a smaller numbers spread across more subdisciplines.

Professor Blei is also a bit of a superstar, so that didn’t hurt.Given the strong interest in the topic, AR could be closer than we think, but we’ll probably use it to layer Groupon deals over shops we pass by instead of building unstoppable fighting machines.This is another machine learning paper and its presence in the top 10 is primarily due to AI, with a small contribution from folks listing neural networks as their discipline, most likely due to the paper being published in IEEE Transactions on Neural Networks.Reinforcement learning is essentially a technique that borrows from biology, where the behavior of an intelligent agent is is controlled by the amount of positive stimuli, or reinforcement, it receives in an environment where there are many different interacting positive and negative stimuli.This is how we’ll teach the robots behaviors in a human fashion, before they rise up and destroy us.Since we recently announced our 001 Binary Battle to promote applications built on the Mendeley API (now including PLo S as well), I decided to take a look at the data to see what people have to work with.My analysis focused on our second largest discipline, Computer Science.If you’re using Mendeley, you’re using both collaborative and content-based discovery methods! I would really have expected this to be at least number 3 or 4, but the strong showing by the AI discipline for the machine learning papers in spots 1, 4, and 5 pushed it down.This paper discusses the theory of sending communications down a noisy channel and demonstrates a few key engineering parameters, such as entropy, which is the range of states of a given communication.Biological Sciences (my discipline) is the largest, but I started with this one so that I could look at the data with fresh eyes, and also because it’s got some really cool papers to talk about.Here’s what I found: What I found was a fascinating list of topics, with many of the expected fundamental papers like Shannon’s Theory of Information and the Google paper, a strong showing from Mapreduce and machine learning, but also some interesting hints that augmented reality may be becoming more of an actual reality soon.


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