Fully automatic deep learning has become the state-of-the-art technique for many tasks
including image acquisition, analysis and interpretation, and for the extraction of clinically …

The key idea behind active learning is that a machine learning algorithm can achieve
greater accuracy with fewer labeled training instances if it is allowed to choose the training …

A large number of 3D models are created and available on the Web, since more and more
3D modelling anddigitizing tools are developed for ever increasing applications. The …

Relevance feedback is often a critical component when designing image databases. With
these databases it is difficult to specify queries directly and explicitly. Relevance feedback …

The paper is concerned with two-class active learning. While the common approach for
collecting data in active learning is to select samples close to the classification boundary …

Recently active learning has attracted a lot of attention in computer vision field, as it is time
and cost consuming to prepare a good set of labeled images for vision data analysis. Most …

Automated annotation of digital pictures has been a highly challenging problem for
computer scientists since the invention of computers. The capability of annotating pictures by …

Three-dimensional shape searching is a problem of current interest in several different
fields. Most techniques have been developed for a particular domain and reduce a shape …

The current exponential increase of spatiotemporally explicit data streams from satellite-
based Earth observation missions offers promising opportunities for global vegetation …

Active learning sequentially selects unlabeled instances to label with the goal of reducing
the effort needed to learn a good classifier. Most previous studies in active learning have …