arXiv subjects

Anton Stepanov

Publications and source records attributed to Anton Stepanov.

5 recordsLinked to original sources

arXiv2021

AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors

The emerging progress of eSports lacks the tools for ensuring high-quality analytics and training in Pro and amateur eSports teams. We report on an Artificial Intelligence (AI) enabled solution for predicting the eSports player in-game performance using exclusively the data from sensors. For this reason, we collected the physiological, environmental, and the game chair data from Pro and amateur players. The player performance is assessed from the game logs in a multiplayer game for each moment of time using a recurrent neural network. We have investigated that attention mechanism improves the generalization of the network and provides the straightforward feature importance as well. The best model achieves ROC AUC score 0.73. The prediction of the performance of particular player is realized although his data are not utilized in the training set. The proposed solution has a number of promising applications for Pro eSports teams and amateur players, such as a learning tool or a performance monitoring system.

cs.HC↗

arXiv2021

Ion implantation in \b{eta}-Ga2O3: physics and technology

Gallium oxide and in particular its thermodynamically stable \b{eta}-Ga2O3 phase is within the most exciting materials in research and technology nowadays due to its unique properties, such as an ultra-wide band gap and a very high breakdown electric field, finding a number of applications in electronics and optoelectronics. Ion implantation is a traditional technological method used in these fields, and its well-known advantages can contribute greatly to the rapid development of physics and technology of Ga2O3-based materials and devices. Here, the current status of ion beam implantation in \b{eta}-Ga2O3 is reviewed. The main attention is paid to the results of experimental study of damage under ion irradiation and the properties of Ga2O3 layers doped by ion implantation. The results of ab initio theoretical calculations of the impurities and defects parameters are briefly presented, and the physical principles of a number of analytical methods used to study implanted gallium oxide layers are highlighted. The use of ion implantation in the development of such Ga2O3-based devices as metal oxide field effect transistors, Schottky barrier diodes, and solar-blind UV detectors, is described together with systematical analysis of the achieved values of their characteristics. Finally, the most important challenges to be overcome in this field of science and technology are discussed.

cond-mat.mtrl-sci↗

arXiv2019

Esports Athletes and Players: a Comparative Study

We present a comparative study of the players' and professional players' (athletes') performance in Counter Strike: Global Offensive (CS:GO) discipline. Our study is based on ubiquitous sensing helping identify the biometric features significantly contributing to the classification of particular skills of the players. The research provides better understanding why the athletes demonstrate superior performance as compared to other players.

cs.HC↗

arXiv2019

Towards Understanding of eSports Athletes' Potentialities: The Sensing System for Data Collection and Analysis

eSports is a developing multidisciplinary research area. At present, there is a lack of relevant data collected from real eSports athletes and lack of platforms which could be used for the data collection and further analysis. In this paper, we present a sensing system for enabling the data collection from professional athletes. Also, we report on the case study about collecting and analyzing the gaze data from Monolith professional eSports team specializing in Counter-Strike: Global Offensive (CS:GO) discipline. We perform a comparative study on assessing the gaze of amateur players and professional athletes. The results of our work are vital for ensuring eSports data collection and the following analysis in the scope of scouting or assessing the eSports players and athletes.

cs.HC↗

arXiv2019

Sensors and Game Synchronization for Data Analysis in eSports

eSports industry has greatly progressed within the last decade in terms of audience and fund rising, broadcasting, networking and hardware. Since the number and quality of professional team has evolved too, there is a reasonable need in improving skills and training process of professional eSports athletes. In this work, we demonstrate a system able to collect heterogeneous data (physiological, environmental, video, telemetry) and guarantying synchronization with 10 ms accuracy. In particular, we demonstrate how to synchronize various sensors and ensure post synchronization, i.e. logged video, a so-called demo file, with the sensors data. Our experimental results achieved on the CS:GO game discipline show up to 3 ms accuracy of the time synchronization of the gaming computer.

cs.HC↗