Australian deep learning startup wins over IP Australia after conquering Europe

Photo: Ex Machina/ IMDb.

Australian startup TrademarkVision has won a major deal in its home country just weeks after conquering Europe with its deep learning algorithm.

Assistant minister for innovation Craig Laundy will announce that IP Australia has agreed to integrate TrademarkVision’s image recognition technology into the government agency’s new Australian Trade Mark Search engine.

The assistant minister is launching Australian Trade Mark Search at the Pause Festival in Melbourne today, where the announcement will be made.

Prior to TrademarkVision and IP Australia’s new search tool, users had to describe images in words to find matches.

“The ability to find similar trademark images is an essential part of the [trademark] application process,” said IP Australia director-general Patricia Kelly.

“We anticipate that providing an effective, easy-to-use search tool will lead to better quality trademark applications that are more likely to succeed. This has benefits for IP Australia and our customers, especially small businesses and sole operators — and even our professional attorney customers.”

TrademarkVision, an early beneficiary of QUT Creative Enterprise Australia’s creative-tech startup fund, has developed technology that “mimics the problem solving networks of the human brain” and had won its first government deal with the European Union Intellectual Property Office in December.

Integrated into IP Australia’s new search tool, TrademarkVision’s software must harvest results within seconds from a database of more than 400,000 trademark applications.

Back in December, TrademarkVision founder and chief executive Sandra Mau said that it took a year to develop the deep learning algorithm that has now proved to be so commercially successful.

“We’ve focused on machine learning techniques so the system can recognise objects in trademarks and logos much like humans do. Despite the wide variety of ways humans pictorially depict objects in logos, deep learning has helped to solve this semantic challenge in a quick and robust way,” Mau said at the time.

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