Application of improved least-square generative adversarial networks for rail crack detection by AE technique.

•An improved LSGANs is proposed to detect rail crack signal under noise interference.•MSE is added to the generator loss as a regularization.•LSGANs is modified into a conditional version to obtain samples’ latent details.•Proposed method is testified to eliminate statistical noise and mechanical noise.•The mechanical noise is acquired from the real operating environment of railway.