Additional resources

More detailed information about PeriCoDe/SALIC can be found in:

E. Chatzilari, S. Nikolopoulos, Y. Kompatsiaris and J. Kittler, “SALIC: Social Active Learning for Image Classification,” in IEEE Transactions on Multimedia, vol. 18, no. 8, pp. 1488-1503, Aug. 2016. (URL:
Maronidis, A. et al. (2016). PERICLES Deliverable D4.3: Content Semantics and Use Context Analysis Techniques.

Although PeriCoDe addresses a very important problem in automatic image annotation, the collection of annotated training data is only one aspect of the process: the other part is the training of a classifier using these data in order to annotate – or classify – unseen images. This is known as machine learning and is performed in the test implementation of SALIC’s wrapper.m – to learn more about this, the interested reader should explore the following (non exhaustive list of) resources: