In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
Object localization has applications in many areas of engineering and science. The goal is to spatially locate an arbitrarily-shaped object. In many applications, it is desirable ...
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
Proteomic profiling based on mass spectrometry is an important tool for studies at the protein and peptide level in medicine and health care. Thereby, the identification of releva...
Frank-Michael Schleif, Thomas Villmann, Barbara Ha...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...