Cargando…

A Deep Neural Network-Based Model for Quantitative Evaluation of the Effects of Swimming Training

This paper analyzes the quantitative assessment model of the swimming training effect based on the deep neural network by constructing a deep neural network model and designing a quantitative assessment model of the swimming training effect. This paper addresses the problem of not considering the in...

Descripción completa

Detalles Bibliográficos
Autores principales:	Hou, Jun-Jie, Tian, Hui-Li, Lu, Biao
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Hindawi 2022
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9546648/ https://www.ncbi.nlm.nih.gov/pubmed/36210996 http://dx.doi.org/10.1155/2022/5508365

Ejemplares similares

Modelling Training Adaptation in Swimming Using Artificial Neural Network Geometric Optimisation
por: Carrard, Justin, et al.
Publicado: (2020)

A Quantitative Model of International Trade Based on Deep Neural Network
por: Huang, Xiaoxin, et al.
Publicado: (2022)

Prediction of exercise sudden death in rabbit exhaustive swimming using deep neural network
por: Zhang, Yao, et al.
Publicado: (2021)

Training deep quantum neural networks
por: Beer, Kerstin, et al.
Publicado: (2020)

Training Deep Spiking Neural Networks Using Backpropagation
por: Lee, Jun Haeng, et al.
Publicado: (2016)

Strength Training in Swimming
por: Wirth, Klaus, et al.
Publicado: (2022)

Deep physical neural networks trained with backpropagation
por: Wright, Logan G., et al.
Publicado: (2022)

Quantitative evaluation of deep convolutional neural network-based image denoising for low-dose computed tomography
por: Usui, Keisuke, et al.
Publicado: (2021)

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures
por: Lee, Chankyu, et al.
Publicado: (2020)

Fluorescence microscopy datasets for training deep neural networks
por: Hagen, Guy M, et al.
Publicado: (2021)

DeepSF: deep convolutional neural network for mapping protein sequences to folds
por: Hou, Jie, et al.
Publicado: (2018)

A network for swimming
por: Chew, Yee Lian, et al.
Publicado: (2017)

Acute and Long-Term Effects of Concurrent Resistance and Swimming Training on Swimming Performance
por: Arsoniadis, Gavriil, et al.
Publicado: (2022)

Swimming Training Reduces Neuroma Pain by Regulating Neurotrophins
por: TIAN, JINGE, et al.
Publicado: (2018)

Construction and Evaluation of Intelligent Medical Diagnosis Model Based on Integrated Deep Neural Network
por: Ma, Lina, et al.
Publicado: (2021)

Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition
por: Zhang, Hua, et al.
Publicado: (2021)

Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction
por: Watanabe, Eiji, et al.
Publicado: (2018)

Automated Training of Deep Convolutional Neural Networks for Cell Segmentation
por: Sadanandan, Sajith Kecheril, et al.
Publicado: (2017)

Automatic ICD-10 Coding and Training System: Deep Neural Network Based on Supervised Learning
por: Chen, Pei-Fu, et al.
Publicado: (2021)

A Deep Ultraviolet Mode-locked Laser Based on a Neural Network
por: Lu, Haoyuan, et al.
Publicado: (2020)

Construction of Sports Training Performance Prediction Model Based on a Generative Adversarial Deep Neural Network Algorithm
por: Li, Gang
Publicado: (2022)

The Effects of Two Different Resisted Swim Training Load Protocols on Swimming Strength and Performance
por: González Ravé, José María, et al.
Publicado: (2018)

Quality versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches
por: Nugent, Frank J, et al.
Publicado: (2017)

Probabilistic Models with Deep Neural Networks
por: Masegosa, Andrés R., et al.
Publicado: (2021)

Digital Hologram Watermarking Based on Multiple Deep Neural Networks Training Reconstruction and Attack
por: Kang, Ji-Won, et al.
Publicado: (2021)

Design of Sports Training Simulation System for Children Based on Improved Deep Neural Network
por: Wang, Xuesheng, et al.
Publicado: (2022)

Early Diagnosis and Quantitative Analysis of Stages in Retinopathy of Prematurity Based on Deep Convolutional Neural Networks
por: Li, Peng, et al.
Publicado: (2022)

Linear leaky-integrate-and-fire neuron model based spiking neural networks and its mapping relationship to deep neural networks
por: Lu, Sijia, et al.
Publicado: (2022)

Assessing protein model quality based on deep graph coupled networks using protein language model
por: Liu, Dong, et al.
Publicado: (2023)

Quantitative evaluation of explainable graph neural networks for molecular property prediction
por: Rao, Jiahua, et al.
Publicado: (2022)

Intelligent Performance Evaluation of Urban Subway PPP Project Based on Deep Neural Network Model
por: Fan, Weizhi, et al.
Publicado: (2022)

Hands-on deep learning for IoT: train neural network models to develop intelligent IoT applications
por: Karim, Rezaul, et al.
Publicado: (2019)

Exploring deep neural networks via layer-peeled model: Minority collapse in imbalanced training
por: Fang, Cong, et al.
Publicado: (2021)

Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices
por: Gokmen, Tayfun, et al.
Publicado: (2017)

Swimming Phase-Based Performance Evaluation Using a Single IMU in Main Swimming Techniques
por: Hamidi Rad, Mahdi, et al.
Publicado: (2021)

Adaptations to Swimming Training in Athletes with Down’s Syndrome
por: González-Ravé, José María, et al.
Publicado: (2020)

Effects of swimming training on myocardial protection in rats
por: Lai, Chang-Chi, et al.
Publicado: (2022)

Quantitative salivary gland SPECT/CT using deep convolutional neural networks
por: Park, Junyoung, et al.
Publicado: (2021)

Quantitative Analysis of Metallographic Image Using Attention-Aware Deep Neural Networks
por: Xu, Yifei, et al.
Publicado: (2020)

Training deep neural density estimators to identify mechanistic models of neural dynamics
por: Gonçalves, Pedro J, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_boirhrqrm362fv86camnvj56up