Computer Sciences

Distilled 3-D (D3D) networks for video action recognition

A team of researchers at Google, the University of Michigan and Princeton University have recently developed a new method for video action recognition. Video action recognition entails identifying particular actions performed ...

Computer Sciences

A new approximate computing approach using CNNs

Researchers at Fukuoka University, in Japan, have recently proposed a design methodology for configurable approximate arithmetic circuits. As part of their study, published on ResearchGate, they applied their method to a ...

Computer Sciences

Computer vision in the dark using recurrent CNNs

Over the past few years, classical convolutional neural networks (cCNNs) have led to remarkable advances in computer vision. Many of these algorithms can now categorize objects in good quality images with high accuracy.

Computer Sciences

ColorUNet: A new deep CNN classification approach to colorization

A team of researchers at Stanford University has recently developed a CNN classification method to colorize grayscale images. The tool they devised, called ColorUNet, draws inspiration from U-Net, a fully convolutional network ...

Computer Sciences

An intuitive physics model to predict the effects of a collision

Humans have the innate ability to predict the effect of collisions, merely using their common sense. In many cases, humans can even predict the results of similar collisions in situations in which mass, friction, or other ...

Computer Sciences

A neural network to extract knowledgeable snippets and documents

Every day, millions of articles are published on social media and other platforms, receiving a vast amounts of clicks and shares from users navigating the web. Many of these articles contain useful information that, if extracted, ...

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