This paper presents a method for locating a wireless signal source using signal strength measurements taken along the border of a 256x256-m2 area. The method leverages a deep Residual Neural Network (ResNet) to predict the location of the transmitter within the area of interest. This approach reduces data collection and computational overhead associated with traditional localization methods. The method is validated through simulated data as well as measurements at 2.7 GHz, with an average error of 7.23 m and a standard deviation of 3.32 m.
