28 December 2019

Racial Bias in Facial Recognition Algorithms

Facial-recognition technology is already being used for applications ranging from unlocking phones to identifying potential criminals. Despite advances, it has still come under fire for racial bias: many algorithms that successfully identify white faces still fail to properly do so for people of color. Recently the National Institute of Standards and Technology (NIST) published a report showing how 189 face-recognition algorithms, submitted by 99 developers across the globe, fared at identifying people from different demographics.

Along with other findings, NIST’s tests revealed that many of these algorithms were 10 to 100 times more likely to inaccurately identify a photograph of a black or East Asian face, compared with a white one. In searching a database to find a given face, most of them picked incorrect images among black women at significantly higher rates than they did among other demographics. This report is the third part of the latest assessment to come out of a NIST program called the Face Recognition Vendor Test (FRVT), which assesses the capabilities of different face-recognition algorithms.

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24 December 2019

Brain Senses Touch Beyond Body

Sensing touch through tools is not a new concept, though it has not been extensively investigated. There is evidence that when the sensory brain regions are presented with the same stimulus repeatedly, the responses of the underlying neural population get suppressed. This repetition suppression can be measured and used as a time stamp to signify when a stimulus is extracted in the brain.

Recent results indicate the neural mechanisms for detecting touch location on tools are remarkably like what happens to localize touch on your own body. People could locate touches on a tool quickly and efficiently using the same neural processes for detecting touch on the body. Insensate objects can become, potentially, ways of detecting information from the world and relaying it toward the somatosensory systems.

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22 December 2019

Camera Reads Mind

Panasonic technology is the brain behind a new brain-reading camera that's set to revolutionize neuroscience. The SLICE camera (separated-light contactless extraction) can directly acquire brain functional images using ordinary nanosecond laser diodes and a Panasonic compact camera sensor without an image intensifier or physical probes being attached. That means it can record functional brain imaging using a non-contact, cost-effective and compact setup, as opposed to the expensive, bulky and inefficient imaging traditional brain imaging tools. 


Non-contact acquisition of brain function using a time-extracted compact camera, published on Nature Research traditional optical imaging techniques (such as fMRI equipment) are costly and can only acquire a limited number of images over a small surface area. The SLICE camera employs image sensor-based capture to record two-dimensional distribution of brain blood flow, without requiring contact with the subject. It comprises a pair of 750-nm laser diode made by Sharp, along with a pair of 855-nm laser diodes manufactured by JDSU.

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