Linear scale-space theory provides a useful framework to quantify the differential and integral geometry of spatio-temporal input images. In this paper that geometry comes about by...
Alfons H. Salden, Bart M. ter Haar Romeny, Max A. ...
—Compressed Sensing (CS) is a novel sampling paradigm that tries to take data-compression concepts down to the sampling layer of a sensory system. It states that discrete compres...
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...
—In this paper, we describe oCast, an energy-optimal multicast routing protocol for wireless sensor networks. The general minimum-energy multicast problem is NP-hard. Intermitten...
Lu Su, Bolin Ding, Yong Yang, Tarek F. Abdelzaher,...