標(biāo)題: Titlebook: Individualizing Training Procedures with Wearable Technology; Peter Düking,Billy Sperlich Book 2024 The Editor(s) (if applicable) and The [打印本頁] 作者: 拖累 時(shí)間: 2025-3-21 18:09
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書目名稱Individualizing Training Procedures with Wearable Technology讀者反饋學(xué)科排名
作者: penance 時(shí)間: 2025-3-21 20:24 作者: 使更活躍 時(shí)間: 2025-3-22 03:12 作者: 懸掛 時(shí)間: 2025-3-22 07:54 作者: grieve 時(shí)間: 2025-3-22 11:09 作者: MODE 時(shí)間: 2025-3-22 14:15
A Primer on Wearable Technology for Injury Risk Management in Distance Running,ics and Electronic Music, the Center for Microsystems Technology, and the Internet Technology and Data Science Lab). The presented findings offer a better understanding to runners, coaches, and clinicians who may want to encourge impact reduction in runners. I hasten to add that this chapter is mere作者: exceed 時(shí)間: 2025-3-22 18:27 作者: Allure 時(shí)間: 2025-3-22 21:15
ng increasingly available and potentially can aid athletes and coaches to individualize and optimize training procedures.?Finally, the book explores if and how data can deliver actionable insights to inform long-term and day-to-day decision making to individualize training procedure..978-3-031-45115-7978-3-031-45113-3作者: Extort 時(shí)間: 2025-3-23 04:56 作者: GIBE 時(shí)間: 2025-3-23 07:44 作者: conscience 時(shí)間: 2025-3-23 12:04 作者: 青春期 時(shí)間: 2025-3-23 14:32
Carlos Balsalobre-Fernández,Manuel Matzkal visual features and high-level semantic features, allowing generating separate palette colors for different objects with similar colors. This enables users to perform targeted local editing, i.e., distinguish and recolor objects with similar colors separately, without producing unexpected global c作者: 貪心 時(shí)間: 2025-3-23 20:37 作者: MIRTH 時(shí)間: 2025-3-23 23:00
Matthew Driller,Ian Dunican,Kari Lambing,Amy Benderlity prediction function from data. We evaluate the proposed method for different powerful FR models on two classical video-based (or template-based) benchmarks IJB-B and YTF. Extensive experiments show that, although the tinyFQnet is much smaller than the others, the proposed method outperforms sta作者: 用手捏 時(shí)間: 2025-3-24 06:25
Christoph Zinnerintra-video and inter-video loss. Moreover, a ranking weight strategy is presented to select high-quality positive and negative pairs during training. Afterward, an effective pseudo-label denoised process is introduced to alleviate the noisy activations caused by the video-level annotations, thereby作者: 脆弱么 時(shí)間: 2025-3-24 06:47
Leon Forcher,Leander Forcher,Stefan Altmannategories to weight different classes, then adaptively leverage the suppression of head classes according to the logit value of the network output. Meanwhile, dynamically adjusting the suppression gradient of the background classes to protect the head and common classes while improving the detection作者: Cognizance 時(shí)間: 2025-3-24 10:47 作者: 青石板 時(shí)間: 2025-3-24 17:34 作者: Immunotherapy 時(shí)間: 2025-3-24 22:59
Individualizing Training Procedures with Wearable Technology978-3-031-45113-3作者: 使迷醉 時(shí)間: 2025-3-25 01:45
,Sensor Data from Wearable Technologies to Inform Decision-Making to?Individualize Training?Procedur in response to different training stimuli, transferability of training procedures between athletes or applying?the same training?stimuli at different time points?to the same atletes is impaired. In order to make the right decision during training procedures for the individual, athletes and their co作者: doxazosin 時(shí)間: 2025-3-25 04:29
How Data Can Capture Recovery: The Case for Heart Rate Variability,, a vast body of literature has investigated the impact of acute and chronic stressors on HRV. Technological advancements such as mobile apps and wearables able to capture HRV data in more practical settings have further pushed the adoption and use of HRV analysis. In this chapter, we cover the phys作者: 功多汁水 時(shí)間: 2025-3-25 08:30
How Sensor Data Can Guide Intensity in Resistance Training Procedures,tionally, resistance training programs are designed by prescribing relative intensities as a percentage of the individual’s one-repetition maximum for a predetermined number of sets and repetitions. However, this traditional approach fails to account for daily fluctuations in the athlete’s strength 作者: 背叛者 時(shí)間: 2025-3-25 14:55 作者: A精確的 時(shí)間: 2025-3-25 18:39
How Sensor Data Can Guide Sleep Behaviors in Athletes,nted rings through to at-home polysomnography devices. Alongside these developments in sleep technologies, there have been concomitant increases in the monitoring of sleep in athletic populations, both in the research and practical settings. The increase in sleep monitoring in sport is likely due to作者: 哀悼 時(shí)間: 2025-3-25 20:03 作者: 譏諷 時(shí)間: 2025-3-26 01:43 作者: 吝嗇性 時(shí)間: 2025-3-26 05:41
cations to Humanoid, Deep-sea-application to Space application, and Industry applications to Man-less-plant. Today’s technologies demand to produce intelligent machine, which are enabling applications in various domains and services. Robotics is one such area which encompasses number of technology i作者: narcotic 時(shí)間: 2025-3-26 11:30
Peter Düking,Billy Sperlich active forensic methods, such as digital watermarking or digital signatures, fail or are not present. The NIDIF for lossy JPEG compressed images are of special importance due to its pervasively use in many applications. Recently, researchers showed that certain types of tampering manipulations can 作者: 擺動(dòng) 時(shí)間: 2025-3-26 14:47
Marco Altinipulating a small set of representative colors. Many approaches have been proposed for palette extraction and palette-based image recoloring. However, existing methods primarily leverage low-level visual information to extract color palettes, so that different objects with similar colors will share t作者: discord 時(shí)間: 2025-3-26 20:41 作者: harmony 時(shí)間: 2025-3-26 22:58
Pieter Van den Berghe labeling the temporal boundaries, weakly-supervised methods have drawn increasing attention. Most of the weakly-supervised methods heavily rely on aligning the visual and textual modalities, ignoring modeling the confusing snippets within a video and non-discriminative snippets across different vid作者: 不可思議 時(shí)間: 2025-3-27 04:42
Matthew Driller,Ian Dunican,Kari Lambing,Amy Benders, face images are acquired from a sequence with huge intra-variations. These intra-variations, which are mainly affected by low-quality face images, cause instability of recognition performance. Previous works have focused on ad-hoc methods to select frames from a video or use face image quality as作者: Flounder 時(shí)間: 2025-3-27 05:33
Christoph Zinner labeling the temporal boundaries, weakly-supervised methods have drawn increasing attention. Most of the weakly-supervised methods heavily rely on aligning the visual and textual modalities, ignoring modeling the confusing snippets within a video and non-discriminative snippets across different vid作者: LAITY 時(shí)間: 2025-3-27 10:00 作者: 反對(duì) 時(shí)間: 2025-3-27 17:02 作者: BAIL 時(shí)間: 2025-3-27 20:56
ing procedures.Offers a holistic view on athlete physiology .This book gives evidence-based background information and advice to athletes and coaches on if and how data from wearable technologies can be applied for preparing individual training procedures to achieve improvement on aspects of perform作者: 藝術(shù) 時(shí)間: 2025-3-27 23:55
How Sensor Data Can Guide Females Through Training and Recovery According to Their Menstrual Cycle,in which phase of the menstrual cycle (i.e., hormonal state) they are in order to plan their training according to their hormonal constellation. In practice two parameters (i.e., body temperature and heart rate) are obtainable by wearables and provide information about the time course of the menstrual cycle.作者: 哄騙 時(shí)間: 2025-3-28 03:17 作者: 包裹 時(shí)間: 2025-3-28 09:58
How Sensor Data Can Guide Sleep Behaviors in Athletes,eing used to monitor sleep in the sport setting, evaluate the role that wearables may play in guiding behavior change in athletes, and identify some of the limitations of sleep wearables in the sport and athlete setting. We also provide some case-study examples from the elite sport setting where wearable devices have been used with athletes.
