Search Results for author: Mojtaba Hosseini

Found 6 papers, 3 papers with code

Beyond Suspension: A Two-phase Methodology for Concluding Sports Leagues

no code implementations29 Mar 2024 Ali Hassanzadeh, Mojtaba Hosseini, John G. Turner

Methodology: We propose a data-driven model which exploits predictive and prescriptive analytics to produce a schedule for the remainder of the season comprised of a subset of originally-scheduled games.

Scheduling Stochastic Optimization

RoboCup 2019 AdultSize Winner NimbRo: Deep Learning Perception, In-Walk Kick, Push Recovery, and Team Play Capabilities

2 code implementations16 Dec 2019 Diego Rodriguez, Hafez Farazi, Grzegorz Ficht, Dmytro Pavlichenko, Andre Brandenburger, Mojtaba Hosseini, Oleg Kosenko, Michael Schreiber, Marcel Missura, Sven Behnke

Individual and team capabilities are challenged every year by rule changes and the increasing performance of the soccer teams at RoboCup Humanoid League.

Robotics

NimbRo Robots Winning RoboCup 2018 Humanoid AdultSize Soccer Competitions

1 code implementation5 Sep 2019 Hafez Farazi, Grzegorz Ficht, Philipp Allgeuer, Dmytro Pavlichenko, Diego Rodriguez, Andre Brandenburger, Mojtaba Hosseini, Sven Behnke

Over the past few years, the Humanoid League rules have changed towards more realistic and challenging game environments, which encourage teams to advance their robot soccer performances.

Robotics

NimbRo-OP2X: Adult-sized Open-source 3D Printed Humanoid Robot

1 code implementation19 Oct 2018 Grzegorz Ficht, Hafez Farazi, André Brandenburger, Diego Rodriguez, Dmytro Pavlichenko, Philipp Allgeuer, Mojtaba Hosseini, Sven Behnke

Humanoid robotics research depends on capable robot platforms, but recently developed advanced platforms are often not available to other research groups, expensive, dangerous to operate, or closed-source.

Robotics

Real-Time Anomaly Detection and Localization in Crowded Scenes

no code implementations21 Nov 2015 Mohammad Sabokrou, Mahmood Fathy, Mojtaba Hosseini, Reinhard klette

In this paper, we propose a method for real-time anomaly detection and localization in crowded scenes.

Anomaly Detection

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