標(biāo)題: Titlebook: Artificial Intelligence in Sports, Movement, and Health; Carlo Dindorf,Eva Bartaguiz,Michael Fr?hlich Book 2024 The Editor(s) (if applicab [打印本頁] 作者: 威風(fēng) 時(shí)間: 2025-3-21 17:20
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書目名稱Artificial Intelligence in Sports, Movement, and Health網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Artificial Intelligence in Sports, Movement, and Health被引頻次
書目名稱Artificial Intelligence in Sports, Movement, and Health被引頻次學(xué)科排名
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書目名稱Artificial Intelligence in Sports, Movement, and Health讀者反饋
書目名稱Artificial Intelligence in Sports, Movement, and Health讀者反饋學(xué)科排名
作者: 帳單 時(shí)間: 2025-3-21 23:12
Advancing Endurance Sports with Artificial Intelligence: Application-Focused Perspectives refinement. In a professional context, where personalized training has long been the norm, the value lies in AI‘s capacity to identify weaknesses, providing insights that may surpass traditional coaching methods. This new type of intelligent data analysis can support the coach and the athlete in th作者: cognizant 時(shí)間: 2025-3-22 00:38
Sensors, Internet of Things and Artificial Intelligence for the Diagnosis and Prevention of Falls antisfactory, current AI-based approaches do not address the identification of dedicated fall risk factors in a way that would allow a precise response through specific exercise intervention. Future research should focus on interpretable AI-based concepts that provide a deeper insight into the individ作者: 決定性 時(shí)間: 2025-3-22 06:58
Artificial Intelligence for Sport Injury Predictiones the unique advantages offered by AI-based analyses, and discusses challenges when attempting to utilise AI for injury prediction. Overall, the use of AI for sport injury prediction offers a fascinating opportunity. It may one day create a revolution in the field, improving not only prediction its作者: 民間傳說 時(shí)間: 2025-3-22 10:47
Generative Artificial Intelligence in Anti-doping Analysis in Sportssuccessfully generate synthetic samples that closely resembled real samples, indicating its potential for augmenting datasets used in doping detection. This approach not only enhances the robustness of indirect methods of doping detection by providing a larger dataset for analysis but also addresses作者: Desert 時(shí)間: 2025-3-22 16:27
Transferring Lessons Learned from Uncertainty-Aware Visual Analytics in Clinical Data to Predictive sociated with ML predictions in sports. Drawing upon the knowledge acquired from uncertainty-aware visualization in clinical data, we can lay the groundwork for more resilient and informed applications of ML in the sporting domain.作者: glamor 時(shí)間: 2025-3-22 20:45 作者: 側(cè)面左右 時(shí)間: 2025-3-22 22:32 作者: 繼承人 時(shí)間: 2025-3-23 04:30
Artificial Intelligence in Sports, Movement, and Health作者: Serenity 時(shí)間: 2025-3-23 06:59 作者: puzzle 時(shí)間: 2025-3-23 13:38 作者: misanthrope 時(shí)間: 2025-3-23 15:29 作者: Forsake 時(shí)間: 2025-3-23 19:21 作者: 猜忌 時(shí)間: 2025-3-23 22:32
Behavioral Teratology of Alcoholes the unique advantages offered by AI-based analyses, and discusses challenges when attempting to utilise AI for injury prediction. Overall, the use of AI for sport injury prediction offers a fascinating opportunity. It may one day create a revolution in the field, improving not only prediction its作者: 壓倒 時(shí)間: 2025-3-24 04:33 作者: expound 時(shí)間: 2025-3-24 08:09 作者: Angiogenesis 時(shí)間: 2025-3-24 14:23 作者: 密切關(guān)系 時(shí)間: 2025-3-24 17:40
Yiwen Liu,Xin Xing,Wenxuan Zhongaccuracy in predicting the Men Euro 2020. These accuracies are considered as improvements. The ensemble techniques we previously used on these datasets had an accuracy of 64.9% on the Women US Open 2021 and 67% on the Men Euro 2020.作者: Endometrium 時(shí)間: 2025-3-24 21:08 作者: minaret 時(shí)間: 2025-3-25 00:33 作者: 阻塞 時(shí)間: 2025-3-25 03:40 作者: DEI 時(shí)間: 2025-3-25 10:53 作者: 有罪 時(shí)間: 2025-3-25 13:16
Artificial Intelligence for Sport Injury Prediction seen as equal parts “art” and science. Despite the best efforts of individuals, teams, and national bodies to apply scientifically-derived injury prevention strategies, millions of athletes still get injured in sport every year. Evidently, sport injury prediction is a field, which has scope for imp作者: 無能性 時(shí)間: 2025-3-25 18:39 作者: athlete’s-foot 時(shí)間: 2025-3-25 21:28
A Brief Review of Artificial Intelligence for Sport Informatics in the Scope of Human–Computer Intertal role of Human–Computer Interaction (HCI). Highlighting the surge in AI integration within sports, movement analysis, and health management, we want to underscore its transformative impact on performance analysis, injury prevention, and personalized healthcare interventions. By elucidating the pr作者: Excise 時(shí)間: 2025-3-26 03:20 作者: Ventilator 時(shí)間: 2025-3-26 07:08
Machine Learning in Biomechanics: Enhancing Human Movement Analysisthis context, high-dimensional datasets are typically collected using either laboratory-based biomechanical measurement systems or wearable sensors. In recent years, Machine Learning (ML) has become increasingly popular for exploiting the potential of high-dimensional biomechanical data. There are t作者: Explicate 時(shí)間: 2025-3-26 10:19
Artificial Intelligence-Based Motion Capture: Current Technologies, Applications and Challenges-based approaches, markerless motion capture enables precise tracking and analysis of movements without the need for markers placed on the body. This offers a range of advantages, including improved user-friendliness, greater freedom of movement, and broader applicability in various environments, bo作者: 靈敏 時(shí)間: 2025-3-26 16:41
Machine Learning in Tennissuch as Hawk-Eye, has advanced research in this field. A review of scientific articles shows the recent evolution of Machine Learning (ML) techniques and their potential impact on tennis. Finally, a practical example of a predictive model is presented to demonstrate the process and results of this s作者: archaeology 時(shí)間: 2025-3-26 16:50 作者: 等級的上升 時(shí)間: 2025-3-27 00:00
Learning to Run Marathons: On the Applications of Machine Learning to Recreational Marathon Runninge data can be used to support individuals as they train and compete, focusing in particular on recreational marathon runners. We discuss why the marathon is an interesting data science application domain, and we present several case studies to demonstrate how ideas from machine learning and recommen作者: 設(shè)施 時(shí)間: 2025-3-27 04:01
Data-Driven Methods for Soccer Analysisns and abundant data sources, serves as an ideal canvas for applying these methodologies. The core concept of the chapter revolves around establishing a data-driven pipeline in soccer and sports science. This pipeline automates the collection, transformation, processing, and analysis of data, creati作者: Tartar 時(shí)間: 2025-3-27 06:58 作者: preeclampsia 時(shí)間: 2025-3-27 09:43
Mariana Gonzalez Insua,Edurne Battistaheir validity and applications in sports and health. We complement this literature review by providing two practical examples of our own research and summarize the main challenges that need to be tackled in future research.作者: mosque 時(shí)間: 2025-3-27 15:05
Xiaoming Huo,Cheng Huang,Xuelei Sherry Niionising soccer performance analysis. This chapter covers the promises and possibilities that the confluence of Artificial Intelligence (AI) and sports science holds, offering a roadmap for optimising athlete and team performance.作者: 極為憤怒 時(shí)間: 2025-3-27 21:47
A Brief Review of Artificial Intelligence for Sport Informatics in the Scope of Human–Computer Interxperiences tailored to individuals’ needs and preferences. Therefore, we provide a brief overview of AI‘s influence on athletic performance, injury management, and healthcare, advocating for human-centered design (HCD) principles to optimize user engagement and outcomes in this dynamic domain.作者: 哀悼 時(shí)間: 2025-3-28 01:53 作者: Soliloquy 時(shí)間: 2025-3-28 04:43 作者: Inveterate 時(shí)間: 2025-3-28 08:15 作者: Panacea 時(shí)間: 2025-3-28 13:13 作者: 多樣 時(shí)間: 2025-3-28 15:17
Book 2024 were brought together, offering diverse perspectives and applications across various disciplines. Through the examination of real-world use cases and future possibilities, this book empowers readers with knowledge, enhancing the understanding of the transformative potential of AI in sports, movement, and health..作者: Debate 時(shí)間: 2025-3-28 22:25
Handbook of Behavioral Medicinemportant criterion for scientific success, whereas the capability for explanation is seriously diminished. Finally, the chapter explores how the use of software leads to a new social organization of science.作者: preservative 時(shí)間: 2025-3-29 01:31 作者: crumble 時(shí)間: 2025-3-29 04:20 作者: 歡笑 時(shí)間: 2025-3-29 08:50 作者: 碎片 時(shí)間: 2025-3-29 11:51 作者: 討好女人 時(shí)間: 2025-3-29 16:26
Carlo Dindorf,Eva Bartaguiz,Michael Fr?hlichExplore how cutting-edge AI for sports enhances training, performance analysis, and strategic decision-making.Discover how AI improves injury prevention and promotes overall health management.Uncover 作者: 真實(shí)的你 時(shí)間: 2025-3-29 22:59 作者: FRONT 時(shí)間: 2025-3-30 02:27
Machine Learning in Tennissuch as Hawk-Eye, has advanced research in this field. A review of scientific articles shows the recent evolution of Machine Learning (ML) techniques and their potential impact on tennis. Finally, a practical example of a predictive model is presented to demonstrate the process and results of this study.作者: 表狀態(tài) 時(shí)間: 2025-3-30 05:43
Learning to Run Marathons: On the Applications of Machine Learning to Recreational Marathon Runninge data can be used to support individuals as they train and compete, focusing in particular on recreational marathon runners. We discuss why the marathon is an interesting data science application domain, and we present several case studies to demonstrate how ideas from machine learning and recommender systems can be used to help marathon runners.作者: FLAG 時(shí)間: 2025-3-30 12:06
https://doi.org/10.1007/978-3-031-67256-9Sports and Technology; Machine Learning; Health Management; Deep Learning; Technology
