Collaborating Authors

Monkeywrenching the Machine


Silicon Valley's surveillance-based business model relies heavily on machine learning. But with the right techniques, we can resist the enclosure of our lives for profit and disrupt the disruptors.

Microsoft tweaks facial-recognition tech to combat bias

FOX News

Microsoft's facial-recognition technology is getting smarter at recognizing people with darker skin tones. On Tuesday, the company touted the progress, though it comes amid growing worries that these technologies will enable surveillance against people of color. Microsoft's announcement didn't broach the concerns; the company merely addressed how its facial-recognition tech could misidentify both men and women with darker skin tones. Microsoft has recently reduced the system's error rates by up to 20 times. In February, research from MIT and Stanford University highlighted how facial-recognition technologies can be built with bias.

Active Gesture Recognition using Learned Visual Attention

Neural Information Processing Systems

We have developed a foveated gesture recognition system that runs in an unconstrained office environment with an active camera. Using visionroutines previously implemented for an interactive environment, wedetermine the spatial location of salient body parts of a user and guide an active camera to obtain images of gestures or expressions. A hidden-state reinforcement learning paradigm is used to implement visual attention. The attention module selects targets to foveate based on the goal of successful recognition, and uses a new multiple-model Q-Iearning formulation. Given a set of target and distractor gestures, our system can learn where to foveate to maximally discriminate a particular gesture. 1 INTRODUCTION Vision has numerous uses in the natural world.

These patterned glasses are all it takes to fool AI-powered facial recognition ZDNet

AITopics Original Links

The researchers have shown how it's possible to perturb facial recognition with patterned eyeglass frames. Researchers have developed patterned eyeglass frames that can trick facial-recognition algorithms into seeing someone else's face. The printed frames allowed three researchers from Carnegie Mellon to successfully dodge a facial-recognition system based on machine-learning 80 percent of the time. Using certain variants of the frames, a white male was also able to fool the algorithm into mistaking him for movie actress Milla Jovovich, while a South-Asian female tricked it into seeing a Middle Eastern male. A look at some of the best IoT and smart city projects which aim to make the lives of citizens better.

AI-enabled image recognition system to revolutionize the manufacturing line


Working hands-on with this technology for five years with Fujitsu Group companies, Fujitsu Laboratories has made progress improving the productivity, quality, cost and delivery of electronics parts manufacturing. Download our document to learn more.