1. A computer system for characterization of a test object using spatial data, the computer system comprising: a graphical processing unit having a graphical processing memory; a general processor; and general memory addressable by the general processing unit, the general memory storing at least one program for execution by the at least one general processor, the at least one program comprising instructions for: (A) obtaining spatial coordinates for a target object; (B) modeling the test object with the target object in each pose of a plurality of different poses, thereby creating a plurality of voxel maps, wherein each respective voxel map in the plurality of voxel maps comprises the test object in a respective pose in the plurality of different poses; (C) unfolding each voxel map in the plurality of voxel maps into a corresponding vector, thereby creating a plurality of vectors, wherein each vector in the plurality of vectors is the same size; (D) providing the plurality of vectors to the graphical processing unit memory, wherein the graphical processing memory comprises a network architecture that includes an input layer for sequentially receiving the plurality of vectors, a plurality of convolutional layers, and a scorer, wherein the plurality of convolutional layers includes an initial convolutional layer and a final convolutional layer, each layer in the plurality of convolutional layers is associated with a different set of weights, responsive to input of a respective vector in the plurality of vectors, the input layer feeds a first plurality of values into the initial convolutional layer as a first function of values in the respective vector, wherein the first function is computed using the graphical processing unit, each respective convolutional layer, other than the final convolutional layer, feeds intermediate values, as a respective second function of (i) the different set of weights associated with the respective convolutional layer and (ii) input values received by the respective convolutional layer, into another convolutional layer in the plurality of convolutional layers, wherein the second function is computed using the graphical processing unit, and the final convolutional layer feeds final values, as a third function of (i) the different set of weights associated with the final convolutional layer and (ii) input values received by the final convolutional layer that is computed using the graphical processing unit, into the scorer; (E) obtaining a plurality of scores from the scorer, wherein each score in the plurality of scores corresponds to the input of a vector in the plurality of vectors into the input layer; and (F) using the plurality of scores to characterize the test object.