Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
The Level 1 Processing of SMOS transforms the data acquired by MIRAS (Microwave Imaging Radiometer with Aperture Synthesis) into geolocated TOA Brightness Temperatures, providing ...
Antonio Gutierrez, Jose Barbosa, Nuno Catarino, Ri...
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
The increased use of video data sets for multimedia-based applications has created a demand for strong video database support, including efficient methods for handling the content...
Walid G. Aref, Moustafa A. Hammad, Ann Christine C...