Multi-sensor precipitation-classification apparatus and method

A method comprising:

• receiving, by a computer system carried on-board a vehicle, image data captured by a camera oriented so as to be forward or rearward facing with respect to the vehicle, wherein the image data comprises at least one image captured by the camera within a period of time;
• receiving, by the computer system, accelerometer data output by an accelerometer secured to a windshield of the vehicle, wherein the accelerometer data characterizes vibration of the windshield during the period of time;
• receiving, by an artificial neural network run on the computer system, the image data and the accelerometer data as inputs;
• generating, by the artificial neural network, classification scores based on the inputs with respect to at least three classes of meteorological precipitation, the at least three classes comprising rain, hail, and snow;
• and
• controlling, by the computer system, at least one function of the vehicle based on the classification scores generated by the artificial neural network;
• wherein generating the classification scores based on the inputs comprises:
• inputting the image data and accelerometer data to a plurality of classifiers, each classifier of the plurality of classifiers being trained to detect a class of the at least three classes of meteorological precipitation corresponding to the each classifier;
• weighting, by each classifier of the plurality of classifiers, the image data and accelerometer data according to weights of the each classifier such that the weights of one classifier of the plurality of classifiers are different from the weights of another classifier of the plurality of classifiers;
• generating, by each classifier of the plurality of classifiers, a classification score of the classifications scores according to the weights of the each classifier, the image data, and the accelerometer data.