Loveland Innovations launches deep learning engine built specifically for UAS-based inspections


A company called Loveland Innovations has announced the launch of the beta version of IMGING Detect, a “deep learning engine built specifically for drone-based inspections.”

Deep learning is an “advanced approach to artificial intelligence (A.I.) that allows IMGING to “learn” as it gathers more data,” Loveland explains, which makes IMGING “more sophisticated and accurate each time it’s used.”

Loveland says that this capability has “vast implications” for a variety of applications such as, but not limited to, damage detection and object and materials detection. Loveland adds that IMGING’s proprietary damage detection algorithms are the “most advanced currently available” to the UAS-based roof, building and property inspection space.

“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,” says Jim Loveland, CEO and Founder of Loveland Innovations.

“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.”

According to Loveland, IMGING users will be able to inspect a roof or property with an automated UAS, automatically find damage and materials, and create detailed estimates using one tool, all without ever stepping foot on a roof, thanks to the new deep learning framework.

Loveland says that currently, IMGING Detect makes estimating much easier by automatically highlighting areas of damage on inspection images. The initial build can recognize a variety of things, including wind-blown shingles and hail hits, including fringe hail, on composition rooftops.

​For Leif Larson, CTO of Loveland Innovations, this technology is a huge milestone in itself, but he notes that “it’s just the first of many uses Loveland Innovations has planned for deep learning in IMGING.”

“The deep learning framework used in IMGING Detect is foundational technology we’ve built to provide a visionary toolset to anyone who does inspections,” Larson says.

“We’ll give IMGING the ability to find multiple kinds of damage, to analyze property risks, determine materials, detect objects, and make the process of building and property inspections much more streamlined. There’s really no limit to what this technology can do, and we’ll continue rolling out new features fast.”