Automated fingerprint recognition using partial and latent fingerprints employs level 3 features which provide additional information in the absence of sufficient number of level 1 and level 2 features. In this paper, we present a methodology for detecting two level 3 features namely, dots and incipient ridges. Specifically, we have designed a deep convolutional neural network which generates a dot map from the input fingerprint image. Subsequently, post-processing operations are performed on the obtained dot map to identify the coordinates of dots and incipient ridges. The results of our experiments on the publicly available PolyU HRF database demonstrate the effectiveness of the proposed algorithm.