Advanced data analytics solutions provider Loveland Innovations has unveiled its latest development for insurers and adjusters: a deep learning engine for drone-based inspections.
The beta version of Loveland’s IMGING® Detect utilizes deep learning AI, allowing drones running on the system to “learn” as they gather more data, making them more sophisticated and accurate each time they are used.
IMGING’s proprietary damage detection algorithms are “the most advanced currently available to the drone-based roof, building and property inspection space,” Loveland said in a release.
“We’re excited about damage detection, but we’re more excited about deep learning. The framework we’ve built completely steamrolls anything else currently available,” commented Loveland Innovations CEO and founder Jim Loveland.
“A lot of others claim they’re data analytics companies, but their technology really doesn’t live up to the promise,” Loveland continued. “We didn’t take the easy route the way others have. Instead, our team has spent the last two years designing and building the most powerful deep learning system in the property inspection space. This release isn’t just about faster inspections and more accurate estimates, it’s about re-thinking the industry’s entire approach to inspections and estimating. Deep learning is dead center in that vision.”
With the new deep learning engine, IMGING users will be able to inspect a roof or other similar property with an automated drone that gets “smarter” with each use. With enough learning, the drone can scan for damages, identify any anomalous materials, and even create detailed estimates all on its own.
At present, the beta build of IMGING Detect automatically highlights areas of damage on inspection images. The version, at this point, can also recognize wind-blown shingles and hail hits, including fringe hail, on composition rooftops.
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