1. A method for generating a labeled dataset using a convolutional neural net (CNN) trained with an initial dataset, the method comprising: extracting a set of feature vectors from a corresponding set of images based on the trained CNN; clustering the set of feature vectors to identify a set of clusters by setting a clustering threshold for identifying feature vectors in each cluster of the set of clusters, wherein the clustering threshold is an adaptive clustering threshold that is based on at least one of a number of images that are being processed for a particular user, a distribution of the feature vectors within a feature space, and relationships between different individuals identified in the set of images; presenting images of an initial cluster of the set of clusters; receiving an identity of an individual to be associated with the presented images; presenting images from each cluster of a set of neighboring clusters identified from the set of clusters; and based on input received from a user, associating the identity to images of the set of neighboring clusters.