1. A computerized method for machine recognition of objects or events from a remotely controlled, unmanned vehicle, comprising: electronically receiving a signal from a plurality of sensors deployed on the vehicle; determining signal-specific components for partitioning each signal; building sets of independent levels for each received signal representing hierarchal information from the signals, each set containing levels spanning from a lowest information level (i=0), where i is an integer, to a highest information level (i=n), where n is a maximum integer; evaluating each level (i) within its set with its associated signal-specific components; building sets of vector signatures associating each level (i) with its evaluated associated signal-specific components; correcting, via a remote human operator of the vehicle, an accuracy of the vector signatures; combining the sets of vector signatures from each signal to form fused signature vectors; mapping natural language semantics to match the fused signature vectors, beginning at lower levels and increasing until a match is found; assigning unique matched semantics to each level(i); pairing syntaxes with the unique semantics and saving the associated fused signature vectors; and eliminating fused signature vectors that result in non-deterministic matches, wherein resulting sets of fused signature vectors and their syntaxed unique semantics define a transformation of information from the signals into machine generated descriptions of objects or events; and wherein the building sets of independent levels is performed according to: level (i=n) if it contains 2 n ×2 n bits of information; and signal information may be strictly converted from level n to level n−1 according to: ⋃ i = 0 2 n - 1 - 1 ⁢ ⋃ j = 0 2 n - 1 - 1 ⁢ a i , j = ( 1 , δ i , j > threshold 0 , otherwise ; ) where , ⁢ δ i , j = a 2 ⁢ i + 1 , 2 ⁢ j + 1 + a 2 ⁢ i + 2 , 2 ⁢ j + 1 + a 2 ⁢ i + 1 , 2 ⁢ j + 2 + a 2 ⁢ i + 2 , 2 ⁢ j + 2 4 , where variable “a” is a subscripted pixel.