The Artificial Intelligence for Multimedia Information Retrieval (AIMIR) research group of the NeMIS-CNR lab has a long experience in topics related to
- Artificial Intelligence
- Multimedia Information Retrieval
- Computer Vision
- Similarity search on a large scale
We aim at investigating the use of Artificial Intelligence and Deep Learning, for Multimedia Information Retrieval, addressing both, issues of effectiveness and efficiency. Multimedia information retrieval techniques should be able to provide users with pertinent results, fast, on a huge amount of multimedia data.
Application areas of our research results range from cultural heritage to smart tourism, from security to smart cities, from mobile visual search to augmented reality.
Multimedia Information Retrieval
MultiMedia Information Retrieval (MMIR) is a research discipline of computer science that aims at extracting semantic information from multimedia data sources. Data sources include directly perceivable media such as audio, image and video, indirectly perceivable sources such as text, biosignals as well as not perceivable sources such as bioinformation, stock prices, etc. To support the fast and effective retrieval of multimedia information on a huge amount of multimedia data we use the most advanced indexing techniques and metric access methods.
This novel situation is what has given rise to similarity searching, also referred to as content-based or similarity retrieval.