Using Temporal Convolutional Networks to estimate ball possession in soccer games-Reference-Cited by-同舟云学术

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Using Temporal Convolutional Networks to estimate ball possession in soccer games

Published:2023-08 Issue: Volume:223 Page:119780
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Borghesi Matteo,Costa Lorenzo Dusty,Morra Lia^ORCID,Lamberti Fabrizio^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference48 articles.

1. A new method of interpolation and smooth curve fitting based on local procedures;Akima;Journal of the ACM,1970

2. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling;Bai,2018

3. The people tracking every touch, pass and tackle in the world cup;Bialik,2014

4. OpenPose: Realtime multi-person 2D pose estimation using part affinity fields;Cao;IEEE Transactions on Pattern Analysis and Machine Intelligence,2021

5. Quo vadis, action recognition? A new model and the kinetics dataset;Carreira,2017

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1. Synchronizing Object Detection: Applications, Advancements and Existing Challenges;IEEE Access;2024

2. The Evolution of AI in Sports Training: A Literature Review with Emphasis on Badminton;2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS);2023-12-11

3. Load Forecasting with Machine Learning and Deep Learning Methods;Applied Sciences;2023-07-06

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