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Relevant bibliographies by topics / Estimation de la distance

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Academic literature on the topic 'Estimation de la distance'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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Journal articles on the topic "Estimation de la distance"

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Kronenfeld, Barry J. "A Plotless Density Estimator Based on the Asymptotic Limit of Ordered Distance Estimation Values." Forest Science 55, no. 4 (2009): 283–92. http://dx.doi.org/10.1093/forestscience/55.4.283.

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Abstract Estimation of tree density from point-tree distances is an attractive option for quick inventory of new sites, but estimators that are unbiased in clustered and dispersed situations have not been found. Noting that bias of an estimator derived from distances to the kth nearest neighbor from a random point tends to decrease with increasing k, a method is proposed for estimating the limit of an asymptotic function through a set of ordered distance estimators. A standard asymptotic model is derived from the limiting case of a clustered distribution. The proposed estimator is evaluated ag

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Makaremi, Masrour, Rafael Ristor, François de Brondeau, Agathe Choquart, Camille Mengelle, and Bernard N’Kaoua. "Estimation of Distances within Real and Virtual Dental Models as a Function of Task Complexity." Diagnostics 13, no. 7 (2023): 1304. http://dx.doi.org/10.3390/diagnostics13071304.

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Orthodontists have seen their practices evolve from estimating distances on plaster models to estimating distances on non-immersive virtual models. However, if the estimation of distance using real models can generate errors (compared to the real distance measured using tools), which remains acceptable from a clinical point of view, is this also the case for distance estimation performed on digital models? To answer this question, 50 orthodontists (31 women and 19 men) with an average age of 36 years (σ = 12.84; min = 23; max = 63) participated in an experiment consisting of estimating 3 types

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Wartenberg, Constanze, and Per Wiborg. "Precision of Exocentric Distance Judgments in Desktop and Cube Presentation." Presence: Teleoperators and Virtual Environments 12, no. 2 (2003): 196–206. http://dx.doi.org/10.1162/105474603321640941.

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Accuracy of space perception and distance estimation in virtual environments is an important precondition for the reliable use of virtual techniques in the design of products, workplaces, architecture, and production systems. The present study compares the accuracy of exocentric 1 distance estimations that a static perceiver achieves with two virtual presentation techniques: a desktop and an immersive cube presentation. Estimation accuracy in a physical mock-up is used as a point of reference. Subjects estimated exocentric distances in detailed models of a workplace previously unknown to them.

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Nam, Gyeong-Mo, and Eui-Rim Jeong. "Distance Estimation Based on Deep Convolutional Neural Network Using Ultra-Wideband Signals." Journal of Computational and Theoretical Nanoscience 17, no. 7 (2020): 3212–17. http://dx.doi.org/10.1166/jctn.2020.9163.

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Recently, high accuracy localization technique is required to provide indoor location services. The purpose of this paper is to propose a distance estimation technique based on deep convolutional neural network (DCNN) for indoor environments. Among distance estimation techniques based on wireless communication signals, the use of ultra-wideband (UWB) signals has the advantage of high accuracy in the time domain. The proposed distance estimation method uses UWB signals and proposes a new DCNN-based distance estimator. The superiority of the proposed method is confirmed through computer simulati

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Nadeau, Christopher P., and Courtney J. Conway. "Field evaluation of distance-estimation error during wetland-dependent bird surveys." Wildlife Research 39, no. 4 (2012): 311. http://dx.doi.org/10.1071/wr11161.

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Context The most common methods to estimate detection probability during avian point-count surveys involve recording a distance between the survey point and individual birds detected during the survey period. Accurately measuring or estimating distance is an important assumption of these methods; however, this assumption is rarely tested in the context of aural avian point-count surveys. Aims We expand on recent bird-simulation studies to document the error associated with estimating distance to calling birds in a wetland ecosystem. Methods We used two approaches to estimate the error associat

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Witmer, Bob G., and Paul B. Kline. "Judging Perceived and Traversed Distance in Virtual Environments." Presence: Teleoperators and Virtual Environments 7, no. 2 (1998): 144–67. http://dx.doi.org/10.1162/105474698565640.

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The ability to accurately estimate distance is an essential component of navigating large-scale spaces. Although the factors that influence distance estimation have been a topic of research in real-world environments for decades and are well known, research on distance estimation in virtual environments (VEs) has only just begun. Initial investigations of distance estimation in VEs suggest that observers are less accurate in estimating distance in VEs than in the real world (Lampton et al., 1995). Factors influencing distance estimates may be divided into those affecting perceived distance (vi

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Givon-Benjio, Nur, Tom Marx, Marissa Hartston, Idan M. Aderka, Bat-Sheva Hadad, and Hadas Okon-Singer. "The relationship between interpersonal distance preference and estimation accuracy in autism." PLOS ONE 19, no. 9 (2024): e0306536. http://dx.doi.org/10.1371/journal.pone.0306536.

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People naturally seek an interpersonal distance that feels comfortable, striking a balance between not being too close or too far from others until reaching a state of equilibrium. Previous studies on interpersonal distance preferences among autistic individuals have yielded inconsistent results. Some show a preference for greater distance, while others indicate a preference for shorter distances, or reveal higher variance in preferences among autistic individuals. In a related vein, previous studies have also investigated the way autistics accurately judge distance, and these studies have rec

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Yoon, Jeonghyeon, Jisoo Oh, and Seungku Kim. "Transfer Learning Approach for Indoor Localization with Small Datasets." Remote Sensing 15, no. 8 (2023): 2122. http://dx.doi.org/10.3390/rs15082122.

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Indoor pedestrian localization has been the subject of a great deal of recent research. Various studies have employed pedestrian dead reckoning, which determines pedestrian positions by transforming data collected through sensors into pedestrian gait information. Although several studies have recently applied deep learning to moving object distance estimations using naturally collected everyday life data, this data collection approach requires a long time, resulting in a lack of data for specific labels or a significant data imbalance problem for specific labels. In this study, to compensate f

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Murray, John, Steven Richardson, Keith Joiner, and Graham Wild. "Aiding Depth Perception in Initial Drone Training: Evidence from Camera-Assisted Distance Estimation." Technologies 13, no. 7 (2025): 267. https://doi.org/10.3390/technologies13070267.

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Remotely Piloted Aircraft (RPA) pilots frequently experience difficulties with depth perception, particularly when estimating distances between the drone and environmental obstacles. This study evaluates whether the use of onboard camera imagery can improve exocentric distance estimation accuracy among ab initio drone pilots operating under visual line-of-sight (VLOS) conditions. Two groups of undergraduate students performed distance estimation tasks at 20 and 50 m. One group used direct observation only to estimate the exocentric distance between the drone and an obstacle. The second group,

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Allen, Robert C., Daniel P. McDonald, and Michael J. Singer. "Landmark Direction and Distance Estimation in Large Scale Virtual Environments." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 41, no. 2 (1997): 1213–17. http://dx.doi.org/10.1177/1071181397041002109.

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The current paper describes our classification of errors participants made when estimating direction and distances in a large scale (2000 m × 2000 m) Virtual Environment (VE). Two VE configuration groups (Low or High Interactivity) traversed a 400 m route through one of two Virtual Terrain's (Distinctive or Non-Distinctive or Terrain 1 and 2, respectively) in 100 m increments. The High VE group used a treadmill to move through the VE with head tracked visual displays; the Low VE group used a joystick for movement and visual display control. Results indicate that as experience within either ter

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Dissertations / Theses on the topic "Estimation de la distance"

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Lowe, Karsten. "Distance estimation between transceivers over short distances." Connect to this title online, 2007. http://etd.lib.clemson.edu/documents/1202417257/.

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Tekaya, Souhaiel Ben. "Distance estimation using handheld devices." Monterey, California: Naval Postgraduate School, 2013. http://hdl.handle.net/10945/34753.

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Approved for public release; distribution is unlimited<br>The different capabilities mobile devices can offer in the field of distance estimation for military applications are explored in this thesis. Of particular interest is the potential for using computer vision techniques to estimate distance in an operational military environment. The methods used for this investigation include a review of past literature on computer vision techniques in this domain, as well as an exploration of the different capabilities mobile devices offer in terms of sensors and networking. We present two potential s

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Andrieu, Guillaume. "Estimation par intervalle d'une distance évolutive." Montpellier 2, 1997. http://www.theses.fr/1997MON20233.

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L'objet de cette these est l'etude de la variabilite d'une estimation de la distance evolutive entre deux sequences moleculaires. Apres un bref apercu de l'historique des theories de l'evolution, nous presentons les differentes methodes de reconstruction phylogenetiques. Nous detaillons ensuite l'expression et l'estimation d'une distance evolutive entre deux sequences dans le cadre d'un modele stochastique de l'evolution. Deux methodes sont communement utilisees pour mesurer l'incertitude d'une estimation de la distance evolutive : l'estimation de la variance et le bootstrap. Nous proposons l'

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Lammi, J. (Jouni), P. (Petteri) Moilanen, and A. (Aleksi) Sierilä. "Size and distance estimation in virtual reality." Bachelor's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201906132541.

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Abstract. Interest in virtual reality (VR) has been on the rise in the recent few years. However, it is difficult to create virtual environments which provide realistic perception of scale for their users. We wanted to study how humans perceive scale in VR and ways to improve VR scale perception. We did a pilot test to see how design choices affect distance and height estimation in VR. For pilot tests we had nine test participants. Based on the experience gathered from the pilot test, we designed the main test. For the main test we had 44 participants. The main test showed similar result

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Warwick, Jane. "Selecting tuning parameters in minimum distance estimators." n.p, 2001. http://ethos.bl.uk/.

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Eriksson, Nils. "Estimation of Distance to empty for heavy vehicles." Thesis, Linköping University, Vehicular Systems, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-56905.

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<p>The distance to empty (DTE) for a heavy vehicle is valuable information both forthe driver and the hauler company. The DTE is estimated as the ratio between the current fuel level and a representative mean fuel consumption. This means the fuel consumption is a prediction of the most likely future mean fuel consumption based on earlier data. It is calculated by applying a forgetting filter on the signal of the momentary fuel consumption in the engine. The filter parameter control how many values that contributes to the output. This is a balance between desired robustness and adaptability of

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Gelman, Geoffrey M. (Geoffrey Michael) 1977. "Distance estimation through wavefront curvature in cellular systems." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80537.

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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.<br>Includes bibliographical references (leaves 78-79).<br>by Geoffrey M. Gelman.<br>S.B.and M.Eng.

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Vichare, Nitin Shrikrishna. "Robust Mahalanobis distance in power systems state estimation." Diss., Virginia Tech, 1993. http://hdl.handle.net/10919/40024.

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Huang, Kyman. "DISTANCE ESTIMATION USING OFDM SIGNALS FOR ULTRASONIC POSITIONING." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2147.

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This paper describes a method of estimating distance via Time-of-Flight (TOF) measurement using ultrasonic Orthogonal Frequency Division Multiplexing (OFDM) signals. Using OFDM signals allows the signals and their sub-carriers to remain orthogonal to each other while continuously transmitting. This estimation method is based on the change of phase of a traveling wave as it propagates through a medium (air for ultrasonic signals). By using signals containing multiple tones, the phase change between each frequency component is slightly different. This phase difference is dependent on the distanc

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Campos, Jennifer L. Sun Hong-Jin. "Multisensory integration in the estimation of distance travelled." *McMaster only, 2007.

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Books on the topic "Estimation de la distance"

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1945-, Kauffman Louis H., and Sandin Daniel J, eds. Hypercomplex iterations: Distance estimation and higher dimensional fractals. World Scientific, 2002.

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Schiffer, Robert G. Long-Distance and Rural Travel Transferable Parameters for Statewide Travel Forecasting Models. TRANSPORTATION RESEARCH BOARD, 2012.

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Hiroyuki, Shioya, and Park Chanseok, eds. Statistical inference: The minimum distance approach. Taylor & Francis, 2011.

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Lehtonen, Matti. Transient analysis for ground fault distance estimation in electrical distribution networks. Technical Research Centre of Finland, 1992.

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K, Niall Keith, Armstrong Laboratory (U.S.), and Armstrong Laboratory (U.S.). Aircrew Training Research Division., eds. Distance estimation with night vision goggles: A direct feedback training method. Air Force Materiel Command, Armstrong Laboratory, Human Resources Directorate, 1997.

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6

Koenker, Roger. Momentary lapses: Moment expansions and the robustness of minimum distance estimation. College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1991.

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1931-, Saridis George N., and United States. National Aeronautics and Space Administration., eds. Distance estimation and collision prediction for on-line robotic motion planning. Center for Intelligent Robotic Systems for Space Exploration, Rensselaer Polytechnic Institute, 1991.

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Vassilopoulos, V. An image analysis system for identification and distance estimation of road vehicles. UMIST, 1995.

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Ehrlich, Jennifer A. Effect of viewing conditions on sickness and distance estimation in a virtual environment. U.S. Army Research Institute for the Behavioral and Social Sciences, 2000.

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Wesselman, A. M. The population-sample decomposition method: A distribution-free estimation technique for minimum distance parameters. M. Nijhoff, 1987.

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Book chapters on the topic "Estimation de la distance"

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Nissen, Ivor. "Distance Estimation." In SpringerBriefs in Electrical and Computer Engineering. Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-61658-1_3.

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Kutoyants, Yu. "Minimum Distance Estimation." In Identification of Dynamical Systems with Small Noise. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1020-4_8.

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Canter, David, and Stephen K. Tagg. "Distance estimation in cities." In Readings on the Psychology of Place. Routledge, 2023. http://dx.doi.org/10.4324/9781003313052-7.

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Devroye, Luc, and Gábor Lugosi. "The Minimum Distance Estimate: Examples." In Combinatorial Methods in Density Estimation. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0125-7_8.

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Rezaei, Mahdi, and Reinhard Klette. "Vehicle Detection and Distance Estimation." In Computer Vision for Driver Assistance. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50551-0_7.

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Marsh, William E., Jean-Rémy Chardonnet, and Frédéric Merienne. "Virtual Distance Estimation in a CAVE." In Spatial Cognition IX. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11215-2_25.

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Buckland, S. T., E. A. Rexstad, T. A. Marques, and C. S. Oedekoven. "Design-Based Estimation of Animal Density and Abundance." In Distance Sampling: Methods and Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19219-2_6.

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Huang, Ge, Flávia C. Delicato, Paulo F. Pires, and Albert Y. Zomaya. "Probabilistic Distance Estimation in Wireless Sensor Networks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29154-8_39.

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Benlamine, Kaoutar, Younès Bennani, Ahmed Zaiou, Mohamed Hibti, Basarab Matei, and Nistor Grozavu. "Distance Estimation for Quantum Prototypes Based Clustering." In Neural Information Processing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36718-3_47.

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Jiménez, Felipe, and Juan Ruiz. "Automatic Sight Distance Estimation for Overtaking Maneuvers." In Proceedings of the XV Ibero-American Congress of Mechanical Engineering. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-38563-6_22.

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AbstractNew assistance systems, as a preliminary step towards automated driving, require a complete knowledge of the environment. To do this, perception sensors are used, but positioning on digital maps is also a valuable tool as a secondary sensor. In this sense, digital maps must contain increasingly greater precision and detail. A variable that is not usually included is the sight distance, which is conditioned by static and dynamic elements. This paper presents a method for its estimation considering the road geometry and other elements that can interfere with driver or sensors vision such

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Conference papers on the topic "Estimation de la distance"

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Ionici, Cristian-Valentin, Silviu-Dorin Meltiş, and Petru Papazian. "Distance Estimation Using Verilog FPGA Implementation." In 2024 International Symposium on Electronics and Telecommunications (ISETC). IEEE, 2024. https://doi.org/10.1109/isetc63109.2024.10797307.

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Muhovič, Jon, and Janez Perš. "Passive Absolute Distance Estimation for Maritime Navigation." In 2024 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters (MetroSea). IEEE, 2024. https://doi.org/10.1109/metrosea62823.2024.10765704.

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Wang, Liming, Xuanzhi Zhao, Zengli Liu, and Sai Zeng. "DV-hop localization for local distance estimation." In Sixteenth International Conference on Signal Processing Systems (ICSPS 2024), edited by Robert Minasian and Li Chai. SPIE, 2025. https://doi.org/10.1117/12.3060781.

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Cai, Nan, and Pia Bideau. "Active Event Alignment for Monocular Distance Estimation." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00245.

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Pelka, Mathias, Martin Mackenberg, Christian Funda, and Horst Hellbruck. "Optical underwater distance estimation." In OCEANS 2017 - Aberdeen. IEEE, 2017. http://dx.doi.org/10.1109/oceanse.2017.8084898.

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Patil, Nishad, Sandeep Menon, Diganta Das, and Michael Pecht. "Evaluation of Robust Covariance Estimation Techniques for Anomaly Detection of Insulated Gate Bipolar Transistors (IGBT)." In ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. ASMEDC, 2010. http://dx.doi.org/10.1115/smasis2010-3861.

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An approach to detect anomalies in IGBTs is to monitor the collector-emitter current and voltage in application. These current and voltage parameters can then be reduced to a univariate distance measure called the Mahalanobis Distance (MD). The MD values with the use of an appropriate threshold enable anomaly detection of these devices. Mahalanobis distances (MD) are weighted Euclidean distances; the distance of each point from the center of the distribution is weighted by the inverse of the sample variance-covariance matrix. The presence of outliers in the monitored data can lead to the overe

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Wang, Yifan, Jannes Iatropoulos, Silvia Thal, and Roman Henze. "Enhancing Urban AEB Systems: Simulation-Based Analysis of Error Tolerance in Distance Estimation and Road-Tire Friction Coefficients." In 2024 Stuttgart International Symposium. SAE International, 2024. http://dx.doi.org/10.4271/2024-01-2992.

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<div class="section abstract"><div class="htmlview paragraph">AEB systems are critical in preventing collisions, yet their effectiveness hinges on accurately estimating the distance between the vehicle and other road users, as well as understanding road conditions. Errors in distance estimation can result in premature or delayed braking and varying road conditions alter road-tire friction coefficients, affecting braking distances. The integration of advanced sensors like LiDARs has significantly enhanced distance estimation. Cameras and deep neural networks are also employed to est

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Anderson, Paul W., and Pavel Zahorik. "Auditory and visual distance estimation." In 161st Meeting Acoustical Society of America. Acoustical Society of America, 2011. http://dx.doi.org/10.1121/1.3656353.

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Fabrizio, Jonathan, and Severine Dubuisson. "Motion Estimation using Tangent Distance." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4378998.

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Morawiec, Garret, Keith K. Niall, and Kathleen Scullion. "Distance Estimation and Simulation Training." In Tenth International Conference on Computer Modeling and Simulation (uksim 2008). IEEE, 2008. http://dx.doi.org/10.1109/uksim.2008.66.

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Reports on the topic "Estimation de la distance"

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Fluitt, Kim F., Timothy Mermagen, and Tomasz Letowski. Auditory Perception in Open Field: Distance Estimation. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada588823.

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Eslinger, Paul W., and Wayne A. Woodward. Minimum Hellinger Distance Estimation for Normal Models. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada228714.

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Reising, Jack D., and Elizabeth L. Martin. Distance Estimation Training with Night Vision Goggles Under Low Illumination. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada291338.

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Traina, Caetano, Traina Jr., Faloutsos Agma J., and Christos. Distance Exponent: A New Concept for Selectivity Estimation in Metric Trees. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada363780.

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Niall, Keith K., Jack D. Reising, Elizabeth L. Martin, and Marcus H. Gregory. Distance Estimation with Night Vision Goggles: A Direct Feedback Training Method. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada328758.

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Ehrlich, Jennifer A. Effect of Viewing Conditions on Sickness and Distance Estimation in a Virtual Environment. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada393953.

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Jerome, Christian J., and Bob G. Witmer. The Perception and Estimation of Egocentric Distance in Real and Augmented Reality Environments. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada493544.

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Fisker, Peter. High-Resolution Estimation of Rural Poverty: Insights from Ethiopia. Data and Evidence to End Extreme Poverty, 2024. https://doi.org/10.55158/deepwp29.

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High-resolution satellite imagery and machine learning techniques enable precise mapping of rural poverty, as demonstrated in this paper for the case of Ethiopia. Using household survey data with precise GPS coordinates, combined with multiple geospatial datasets, we develop a novel two-stage Random Forest model that first predicts roof materials from satellite imagery and then uses this prediction alongside other geospatial features to estimate household consumption levels. The model achieves high predictive accuracy across different spatial scales, with Spearman correlations between 0.81 and

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Ozeki, Toru, and Donald E. Irish. Estimation of the Concentration-Distance Profile within the Electrochemical Diffusion Layer by Raman Microprobe Spectroscopy. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada219521.

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Stastny, Petr, Robert Roczniok, Daniel Cleather, Martin Musalek, Dominik Novak, and Michal Vagner. Straight speed and acceleration optimal distances and reference values. A systematic review, and meta-analyses. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.5.0010.

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Review question / Objective: To summarize the sprint reference acceleration and speed values for different sprint distances and suggest optimal unification of ice-hockey straight sprint testing. Eligibility criteria: The title and abstract screening was done by two researchers (PS and RR) who selected a set of articles for full text screening, where the inclusion criteria were: 1) male or female ice-hockey players; 2) any cross-sectional or intervention study; 3) tests of ice-hockey sprinting over any distance or any battery of conditioning tests that included straight-line sprints; and, 4) re

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