In the nanometer regime, especially the RF and analog circuits exhibit wide parameter variability, and consequently every chip produced needs to be tested. On-chip Design for Testability (DfT) features, which are meant to reduce test time and cost also suffer from parameter variability. Therefore, RF calibration of all on-chip test structures is mandatory. In this paper, Artificial Neural Networks (ANN) are employed as multivariate regression technique to architect a general RF calibration scheme using DC- instead of RF stimuli. This relaxes the routing requirements on a chip for GHz test signals along with the reduction in test time and cost. The RF detector, a key element of a radio front-end DfT circuitry, designed in 65nm CMOS is used to demonstrate the calibration scheme.