DAMAGE iD has a jump-start on A.I…meet Goutham


I’m Goutham, a dedicated master’s student studying A.I. at Northeastern University. I am currently serving as an A.I. intern at DAMAGEiD, and am passionate about creating new cutting-edge technology to solve real-world challenges.

My journey in the field of artificial intelligence has led me to contribute to the innovative work at DAMAGEiD, where I focus on developing advanced models for damage detection and “carry forward” solutions in the realm of vehicle assessment.

Read more below about these specific models.

Damage Detection Model:

One of our primary accomplishments is the creation of a robust damage detection model. This model is finely tuned to identify various types of damages, from clear-cut scratches and paint scratches to dents, dings, and even more severe issues like breakages. By employing state-of-the-art AI techniques, we’ve empowered our system to provide a comprehensive analysis of vehicle conditions, ensuring a meticulous and accurate assessment of damages.

Carry Forward” Model:

Another achievement is our carry forward model. This intelligent system possesses the remarkable ability to remember existing damages in vehicles. For instance, if a customer rents a car with pre-existing damages and returns it with additional issues, our carry forward model excels at distinguishing between the old and new damages.

This capability enables us to charge customers only transparently and fairly for the damages they’ve incurred during their usage, streamlining the billing process, and enhancing customer satisfaction.

As evident in the provided images, our model adeptly retains the information of previous markings and accurately predicts their positions, even when the perspective of the image is modified. This unique feature ensures that our model preserves details of old damages when the damage detection model is applied to a returning vehicle.

Key points are connected between each set of photos taken. This allows our algorithm to link together different areas of the vehicle – even if the pictures are misaligned.
To verify accuracy, we compared corresponding points marked by a human with that estimated by the algorithm (as seen in red vs. blue “X” above). The above photo shows error rates under 2%.

We hope you’re as proud of this progress as we are at DAMAGE iD…We anticipate its completion and launch this April at the ICRS in Vegas where we will be celebrating our 10th year Anniversary…we’ve come a Looong way, Baby!!