Shutterstock's Data Scientist Kevin Lester Talks Reverse Image Search

International Business Times

Stock photo company Shutterstock introduced reverse image search for desktop earlier this spring. This made it easy for users to search Shutterstock's website with an image, instead of using keywords. Shutterstock's data scientist Kevin Lester, who looks closely at the adoption of these new tools, was able to find out what patterns emerge from the data. In fact, Lester shared with IBTimes, that those who used reverse-image search for searches wound up making more downloads per search than those from a user with a text-based search. "We've found that users who performed at least one reverse image search prior to making a purchase with Shutterstock were 3.49 times more likely to make a subsequent purchase than those who did not," says Lester.


TrademarkVision uses machine learning to make finding logos as easy as a reverse image search

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A company's logo is an important part of its identity, but the processes behind defining, registering, and protecting these trademarks is a convoluted and rather archaic one. A startup called TrademarkVision aims to simplify it by replacing that laborious and arcane process with what amounts to a machine-learning-powered reverse image search. This isn't in some lab, either: the EU just switched their whole image trademark system over to it. Most people probably haven't had to do many trademark and logo searches. Well, why don't you take the USPTO's version for a spin so you know what it's like?


Shutterstock shows machine learning smarts with reverse image search for stock photos

#artificialintelligence

Shutterstock is flexing its AI muscles with the news that the stock photo giant is introducing new computer-vision search smarts to its platform. The company, which is headquartered in New York's Empire State Building, went public back in 2012 and now offers more than 70 million images for bloggers and media outlets -- which can make searching for specific assets challenging. Of course, the trusty old keyword search tool is effective to an extent, but what if you want to find images that are similar to one you have in your possession? Or what if you want alternative images based on color schemes, mood, or shapes? This is where Shutterstock's new reverse image search comes into play.


Shutterstock shows machine learning smarts with reverse image search for stock photos

#artificialintelligence

Shutterstock is flexing its AI muscles with the news that the stock photo giant is introducing new computer-vision search smarts to its platform. The company, which is headquartered in New York's Empire State Building, went public back in 2012 and now offers more than 70 million images for bloggers and media outlets -- which can make searching for specific assets challenging. Of course, the trusty old keyword search tool is effective to an extent, but what if you want to find images that are similar to one you have in your possession? Or what if you want alternative images based on color schemes, mood, or shapes? This is where Shutterstock's new reverse image search comes into play.


Shutterstock boosts its machine-learning credentials with launch of reverse image search on iOS

#artificialintelligence

Stock photo giant Shutterstock is boosting its artificial intelligence (AI) credentials today with the launch of a new reverse image search feature within its iOS app. The New York-based company offers more than 80 million images for bloggers and media outlets, but keyword searches aren't always the most effective way to find images relevant to a story. If you want to search for photos that are similar to ones you already have in your possession, or if you want to find alternative photos based on the shapes, mood, color scheme, and general mise en scène around you, reverse image search comes into play. You can search Shutterstock by using the camera on your iPhone or the photos on your camera roll to find similar images. The launch comes three months after Shutterstock first introduced the feature through its desktop version, though extending it to smartphones does feel like a natural move, given that smartphones are cameras in their own right.