Abstract: A computing device stores a predictive model generated by a neural network training engine. The computing device receives first and second two-dimensional (2D) thermal images comprising temperature measurements from respective first and second infrared (IR) sensors. The first and second images have the same size. An image capturing visual field of the second IR sensor partially overlaps with an image capturing visual field of the first IR sensor. The computing device executes a neural network using a predictive model for generating outputs based on inputs. The inputs comprise the temperature measurements of the first and second images. The outputs comprise horizontal and vertical shifts defining a translation of the second image with respect to the first image. An overlapping area in the first image, having a rectangular shape and overlapping with the second image, is determined using the horizontal and vertical shifts.

Abstract: A computing device stores a predictive model generated by a neural network training engine. The computing device receives first and second two-dimensional (2D) thermal images comprising temperature measurements from respective first and second infrared (IR) sensors. The first and second images have the same size. An image capturing visual field of the second IR sensor partially overlaps with an image capturing visual field of the first IR sensor. The computing device executes a neural network using a predictive model for generating outputs based on inputs. The inputs comprise the temperature measurements of the first and second images. The outputs comprise horizontal and vertical shifts defining a translation of the second image with respect to the first image. An overlapping area in the first image, having a rectangular shape and overlapping with the second image, is determined using the horizontal and vertical shifts.