In this paper we propose PARTfs which adopts a supervised machine learning algorithm, namely partial decision trees, as a method for feature subset selection. In particular, it is...
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
— This article presents a behavioural architecture, the Survival Kit (SK), which allows behaviours to cast their multivalued output by means of constraints over an ’action feat...
In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
We consider Cooperative Intrusion Detection System (CIDS) which is a distributed AIS-based (Artificial Immune System) IDS where nodes collaborate over a peer-to-peer overlay netwo...
Abstract. Since texture is scale dependent, multi-scale techniques are quite useful for texture classification. Scale-space theory introduces multi-scale differential operators. In...
Mehrdad J. Gangeh, Bart M. ter Haar Romeny, C. Esw...
People often recognize 3D objects by their boundary shape. Designing an algorithm for such a task is interesting and useful for retrieving objects from a shape database. In this pa...
In the field of computer vision feature matching in high dimensional feature spaces is a commonly used technique for object recognition. One major problem is to find an adequate s...
A proposed KFCM-based fuzzy classifier was introduced. As for the process of constructing such classifier, firstly, the original sample space is mapped into a high dimensional fea...
We propose a computational framework for learning predictive image features as “biomarkers” for Alzheimer’s Disease discrimination using high-resolutionMagnetic Resonance (M...
Yanxi Liu, Leonid Teverovskiy, Oscar L. Lopez, How...