Machine Learning Systems and Methods for Improved Roof Condition Determination and Scoring from Aerial Imagery

Abstract

Machine learning systems and methods for roof condition determination and scoring from aerial imagery. The system includes an inference module, a labeling module, and a training module. The inference module receives an aerial image of a roof and processes the aerial image using one or more trained neural network models to detect a condition of the roof depicted in the aerial image and to score the condition. The labeling module allows one or more agents to label training data for use in training the one or more neural network models, and the training module trains the one or more neural network models using the labels generated by the labeling module. The one or more neural network models includes a multi-layer neural network model including a backbone network layer and a fully-connected convolutional layer.

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