Multiple-shot person re-identification deals with the problem to build the correspondence between the images of the same person appearing at different sites captured by onsite deployed cameras. The difficulty stems from large within-class but small betweenclass variations caused by the change of person appearance and environment. Traditional methods on feature/signature design and/or distance/d...

The behavior of the “constants”, G, c, h̄, a, e, mi and Λ, considering them as variable, in the framework of a flat cosmological model with FRW symmetries described by a bulk viscous fluid and considering mechanisms of adiabatic matter creation are investigated. Two cases are studied; one with radiation predominance and another of matter predominance. It is found that with the solution obtained ...

conclusions radio-guided localization of non-palpable breast lesions is an acceptable method because of technical facilitation, accurate localization and complete excision with limited complications. so it can be recommended as an alternative method for wire-guided localization. results pathologic results were benign in 90.5% and malignant in 9.5% of patients. post-operative margin of lesion wa...

Contemporary data assimilation often involves more than a million prediction variables. Finite ensemble Kalman filters (EnKF) have been developed by geoscientists. They are successful indispensable tools in science and engineering, because they allow for computationally cheap low ensemble state approximation for extremely large dimensional turbulent dynamical systems. The practical finite ensem...

This manuscript addresses the problem of optimizationbased Simultaneous Localization and Mapping (SLAM), which is of concern when a robot, traveling in an unknown environment, has to build a world model, exploiting sensor measurements. Although the optimization problem underlying SLAM is nonlinear and nonconvex, related work showed that it is possible to compute an accurate linear approximation...

Contemporary data assimilation often involves more than a million prediction variables. Ensemble Kalman filters (EnKF) have been developed by geoscientists. They are successful indispensable tools in science and engineering, because they allow for computationally cheap low ensemble state approximation for extremely large dimensional turbulent dynamical systems. The practical finite ensemble fil...

This paper describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of underwater vehicles while exploiting the inertial sensor information that is routinely available on such platforms. We present a novel strategy for efficiently accessing and maintaining consistent covariance bounds within a SLAM inf...

Discrete geologic features such as faults and highly permeable embedded channels can significantly affect subsurface flow and transport characteristics. Therefore, they must be properly identified, parameterized, and represented in subsurface simulation models. In this work, we use an improved ensemble Kalman filter (EnKF) for history-matching fault network geometry from production data. EnKF i...

A scheme for extracting environment features from 1D range data and their interpretation is presented. Segmentation is done by deciding on a measure of model fidelity which is applied to adjacent groups of measurements. The extraction process is considered to include a subsequent matching step where segments which belong to the same landmark are to be merged while keeping track of those which o...

Localization techniques are commonly used in ensemble-based data assimilation (e.g., the Ensemble Kalman Filter (EnKF) method) because of insufficient ensemble samples. They can effectively ameliorate the spurious long-range correlations between the background and observations. However, localization is very expensive when the problem to be solved is of high dimension (say 106 or higher) for ass...