A plastic eyebrow razor could revolutionize the removal of eyebrow tattoos and other eyebrow tattoos, according to a new study.
The study was published online by the journal PLOS ONE on March 11.
The findings are based on data from the U.S. Department of Defense’s Joint Electronic Health Records (JER), which tracks the location and location of people’s eyebrow tattoos.
The data show that more than 5.7 million people have eyebrows that are covered with tattoos, including some that are so small that they are visible through the skin.
According to the JER, more than two million people are affected by tattoos and their removal can be difficult.
The researchers used a facial recognition technology to see if the tattoos could be easily identified.
“We saw an association between facial recognition and tattoo location and tattoo removal,” study author Alex M. Vaknin, an assistant professor at the University of New Hampshire, told The Huffington Post.
Vaknin and his colleagues analyzed the JERS data from 1,735,857 facial images collected over a two-year period.
They found that people with large tattoos were more likely to have their eyebrows covered with them, with an average of 17.3% of people with tattoos covering their eyebrow.
The researchers also looked at the tattoo removal rates of people who had a total of 4,038,838 tattoos and saw that the vast majority of people had at least one tattoo covering their eyebrows.
Vacuum-sealed plastic eyeglasses were also found to be more effective at removing eyebrow tattoos than vacuum-seal glasses.
“These are very promising findings, but we need to do more studies and more data collection to fully understand how they can be used in the real world,” said study co-author Paul F. Sutter, a professor of human health at the U-M School of Public Health.
While the results show that the results of this study are promising, the researchers acknowledge that the data are limited and they need more data to see how effective the technology is.
“The results suggest that the facial recognition system is not foolproof, but if we can find more good data, we can improve the algorithm further,” Sutter said.
In a follow-up study, the team plans to continue to look at how the facial images of people can be identified.