Variability modelling with feature models is one key technique for specifying the problem space of Software Product Lines (SPLs). To allow for the automatic derivation of a concre...
— Many modern computer vision algorithms are built atop of a set of low-level feature operators (such as SIFT [1], [2]; HOG [3], [4]; or LBP [5], [6]) that transform raw pixel va...
The objective of active recognition is to iteratively collect the next "best" measurements (e.g., camera angles or viewpoints), to maximally reduce ambiguities in recogn...
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
This paper introduces an automated technique for feature location: helping developers map features to relevant source code. Like several other automated feature location technique...