1. A method that detects a presence of desired signals in received signals, comprising: receiving a signal that includes a desired signal and noise; estimating the noise by estimating a noise model, the noise model is determined via minima tracking and previous detection of desired signals; utilizing the received signal and the estimated noise to generate a feature set that comprises a concatenation of features, each feature associated with an atom in a frame, each atom referenced by a frequency/time pair, wherein at least one of the features comprises at least one estimated SNR; employing a convolutional neural network for utilizing the concatenation of the features in the feature set to estimate a frame level posterior probability that is utilized to determine whether the desired signal is present in the received signal; and applying a threshold to the estimated frame level posterior probability to render a decision whether the desired signal is present in the received signal.