We propose an unsupervised method for learning multi-stage hierarchies of sparse convolutional features. While sparse coding has become an increasingly popular method for learning visual features, it is most often trained at the patch level. Applying the resulting filters convolutionally results in highly redundant codes because overlapping patches are encoded in isolation. By training convolut...

Automatic estimation of head pose from a face image is a sub-problem of human face analysis with widespread applications such as gaze direction detection, human computer interaction or video teleconferencing. It can also be integrated in a multi-view face detection and recognition system. Current methods on face pose estimation from a 2D image can be divided into two groups. The first group : g...

Prostate segmentation facilitates prostate cancer detection and can help to diagnose the pathological stage of disease. Segmented anatomical models may also help to improve the outcome of robotic-aided laparoscopic prostatectomy (RALP) by augmented reality image guidance. In this paper, we present a fully automated segmentation pipeline for multi-center and multi-vendor MRI prostate segmentatio...

Isogeometric analysis (IgA) uses the same class of basis functions for both, representing the geometry of the computational domain and approximating the solution. In practical applications, geometrical patches are used in order to get flexibility in the geometrical representation. This multi-patch representation corresponds to a decomposition of the computational domain into non-overlapping sub...

Laser scan matching with grid-based maps is a promising tool for real-time indoor positioning of mobile Unmanned Ground Vehicles (UGVs). While there are critical implementation problems, such as the ability to estimate the position by sensing the unknown indoor environment with sufficient accuracy and low enough latency for stable vehicle control, further development work is necessary. Unfortun...

In Wireless Sensor Networks (WSNs), localization algorithms could be range-based or range-free. The Approximate Point in Triangle (APIT) is a range-free approach. We propose modification of the APIT algorithm and refer as modified-APIT. We select suitable triangles with appropriate distance between anchors to reduce PIT test errors (edge effect and non-uniform placement of neighbours) in APIT a...

In the paper, the parallelization of multi-grid methods for solving second-order elliptic boundary value problems in two-dimensional domains is discussed. The parallelization strategy is based on a non-overlapping domain decomposition data structure such that the algorithm is well-suited for an implementation on a parallel machine with MIMD architecture. For getting an algorithm with a good par...

This paper presents a framework for fault-tolerant distributed mutual exclusion and replica control algorithms utilizing overlapping grid quorums, which are sets constructed with the aid of grid structures. There are two components of the framework: the first one concerns generic representation of grid quorums, and the second one, generic verification of the overlapping properties of grid quoru...

Convolutional Neural Network (CNN) models have become the state-of-the-art for most computer vision tasks with natural images. However, these are not best suited for multi-gigapixel resolution Whole Slide Images (WSIs) of histology slides due to large size of these images. Current approaches construct smaller patches from WSIs which results in the loss of contextual information. We propose to c...