Category Archives: neural networks

Google’s Inception Sees This Turtle as a Gun; Image Recognition Camouflage

The good people at MIT’s Computer Science and Artificial Intelligence Laboratory [CSAIL] have found a way of tricking Google’s InceptionV3 image classifier into seeing a rifle where there actually is a turtle. This is achieved by presenting the classifier with what is called ‘adversary examples’.

Adversary examples are a proven concept for 2D stills. In 2014 [Goodfellow], [Shlens] and [Szegedy] added imperceptible noise to the image of a panda that from then on was classified as gibbon. This method relies on the image being undisturbed and can be overcome by zooming, blurring or rotating the image.

The applicability for real …read more

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Posted in 3d Printer hacks, ai, camouflage, computer vision, Google Inception, image recognition, inception, neural networks, news | Leave a comment

Hardware for Deep Neural Networks

In case you didn’t make it to the ISCA (International Society for Computers and their Applications) session this year, you might be interested in a presentation by [Joel Emer] an MIT  professor and scientist for NVIDIA. Along with another MIT professor and two PhD students ([Vivienne Sze], [Yu-Hsin  Chen], and [Tien-Ju Yang]), [Emer’s] presentation covers hardware architectures for deep neural networks.

The presentation covers the background on deep neural networks and basic theory. Then it progresses to deep learning specifics. One interesting graph shows how neural networks are getting better at identifying objects in images every year and as of …read more

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Catastrophic Forgetting: Learning’s Effect on Machine Minds

What if every time you learned something new, you forgot a little of what you knew before? That sort of overwriting doesn’t happen in the human brain, but it does in artificial neural networks. It’s appropriately called catastrophic forgetting. So why are neural networks so successful despite this? How does this affect the future of things like self-driving cars? Just what limit does this put on what neural networks will be able to do, and what’s being done about it?

The way a neural network stores knowledge is by setting the values of weights (the lines in between the neurons …read more

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From 50s Perceptrons To The Freaky Stuff We’re Doing Today

Things have gotten freaky. A few years ago, Google showed us that neural networks’ dreams are the stuff of nightmares, but more recently we’ve seen them used for giving game character movements that are indistinguishable from that of humans, for creating photorealistic images given only textual descriptions, for providing vision for self-driving cars, and for much more.

Being able to do all this well, and in some cases better than humans, is a recent development. Creating photorealistic images is only a few months old. So how did all this come about?

Perceptrons: The 40s, 50s And 60s

We begin in …read more

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Neural Networks Walk Better Than Humans for Game Animation

Modern day video games have come a long way from Mario the plumber hopping across the screen. Incredibly intricate environments of games today are part of the lure for new gamers and this experience is brought to life by the characters interacting with the scene. However the illusion of the virtual world is disrupted by unnatural movements of the figures in performing actions such as turning around suddenly or climbing a hill.

To remedy the abrupt movements, [Daniel Holden et. al] recently published a paper (PDF) and a video showing a method to greatly improve the real-time character control mechanism. …read more

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Neural Nets And Game Boy Cameras

Released in 1998, the Game Boy camera was perhaps the first digital camera many young hackers got their hands on. Around the time Sony Mavica cameras were shoving VGA resolution pictures onto floppy drives, the Game Boy camera was snapping 256×224 resolution pictures and displaying them on a 190×144 resolution display. The picture quality was terrible, but [Roland Meertens] recently had an idea. Why not use neural networks to turn these Game Boy Camera pictures into photorealistic images?

Neural networks, deep learning, machine learning, or whatever other buzzwords we’re using require training data. In this case, the training data would …read more

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