Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan...
We address the problem of exact signal recovery in frequency domain optical coherence tomography (FDOCT) systems. Our technique relies on the fact that, in a spectral interferomet...
S. Chandra Sekhar, Rainer A. Leitgeb, Martin L. Vi...
Recognition of shapes in images is an important problem in computer vision with application in various medical problems, including robotic surgery and cell analysis. The similarit...
Abstract. In this paper we propose an architecture design methodology to optimize the throughput of MD4-based hash algorithms. The proposed methodology includes an iteration bound ...
We present computational techniques for automatically generating algebraic (polynomial equality) invariants for algebraic hybrid systems. Such systems involve ordinary differentia...