@InProceedings{martina2017, author = {Lux, Mathias and Riegler, Michael and Macstravic, Glenn}, booktitle = {ICMR '17 Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval}, title = {LireSolr: A Visual Information Retrieval Server}, year = {2017}, address = {New Yor New York, USA}, editor = {Sebe, Nicu and Ionescu, Bogdan}, month = {jun}, pages = {3}, publisher = {ACM}, abstract = {In this paper, we present LireSolr, an open source image retrieval server, build on top of the LIRE library and the Apache Solr search server. With LireSolr, visual information retrieval can be run on a server, which allows better distribution of workloads and simplifies applications in several areas including mobile and web. Furthermore, we showcase several example scenarios how LireSolr can be used to point out the broad range of possibilities and applications. The system is easy to install and setup, and the large number of retrieval tools either provided by LIRE or by other Apache Solr is made easily available on the search server. Moreover, our tool demonstrates how predictions from CNNs can easily be used to extend the visual information retrieval functionality.}, doi = {10.1145/3078971.3079014}, isbn10 = {978-1-4503-4701-3}, language = {EN}, location = {Bukarest, Rumänien}, talkdate = {2017.06.08}, talktype = {poster}, url = {https://dl.acm.org/citation.cfm?id=3079014} }