Antonio Jiménez

TL;DR: This paper uses low-performance Micro-Electro-Mechanical inertial sensors attached to the foot of a person, and describes, implements and compares several of the most relevant algorithms for step detection, stride length, heading and position estimation.

TL;DR: This paper describes and implements a Kalman-based framework, called INS-EKF-ZUPT (IEZ), to estimate the position and attitude of a person while walking, which represents an extended PDR methodology (IEz+) valid for operation in indoor spaces with local magnetic disturbances.

TL;DR: This document provides a survey of the mathematical methods currently used for position estimation in indoor local positioning systems (LPS), particularly those based on radiofrequency signals, grouped into four categories: geometry-based methods, minimization of the cost function, fingerprinting, and Bayesian techniques.

TL;DR: A review of previous studies to automate the location of fruit on trees using computer vision methods was performed in this paper, where the main features of these approaches were described, paying special attention to the sensors and accessories used for capturing tree images, the image processing strategy used to detect the fruit, and the results obtained in terms of the correct/false detection rates and the ability to detect fruit independent of its maturity stage.

TL;DR: In this article, the authors fit the power spectra with Harvey-like profiles to retrieve the characteristics of the granulation (time scale tau_gran and power P_gran), which is consistent with the theoretical predictions.