Accès libre

A multifactorial detection model of young children’s physical abnormality based on image recognition technology under the concept of physical and health integration

 et   
03 sept. 2024
À propos de cet article

Citez
Télécharger la couverture

Brock, A., De, S., Smith, S. L., & Simonyan, K. (2021, July). High-performance large-scale image recognition without normalization. In International conference on machine learning (pp. 1059-1071). PMLR. Search in Google Scholar

Zoph, B., Vasudevan, V., Shlens, J., & Le, Q. V. (2018). Learning transferable architectures for scalable image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 8697-8710). Search in Google Scholar

McCay, K. D., Ho, E. S., Shum, H. P., Fehringer, G., Marcroft, C., & Embleton, N. D. (2020). Abnormal infant movements classification with deep learning on pose-based features. IEEE Access, 8, 51582-51592. Search in Google Scholar

Hesse, N., Pujades, S., Romero, J., Black, M. J., Bodensteiner, C., Arens, M., ... & Sebastian Schroeder, A. (2018). Learning an infant body model from RGB-D data for accurate full body motion analysis. In Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st International Conference, Granada, Spain, September 16-20, 2018, Proceedings, Part I (pp. 792-800). Springer International Publishing. Search in Google Scholar

Hesse, N., Pujades, S., Black, M. J., Arens, M., Hofmann, U. G., & Schroeder, A. S. (2019). Learning and tracking the 3D body shape of freely moving infants from RGB-D sequences. IEEE transactions on pattern analysis and machine intelligence, 42(10), 2540-2551. Search in Google Scholar

Sakkos, D., Mccay, K. D., Marcroft, C., Embleton, N. D., Chattopadhyay, S., & Ho, E. S. (2021). Identification of abnormal movements in infants: A deep neural network for body part-based prediction of cerebral palsy. IEEE Access, 9, 94281-94292. Search in Google Scholar

Zhang, T., Jia, W., Yang, B., Yang, J., He, X., & Zheng, Z. (2017). MoWLD: a robust motion image descriptor for violence detection. Multimedia Tools and applications, 76, 1419-1438. Search in Google Scholar

Russel, N. S., & Selvaraj, A. (2021). Gender discrimination, age group classification and carried object recognition from gait energy image using fusion of parallel convolutional neural network. IET Image Processing, 15(1), 239-251. Search in Google Scholar

Qiang, J., Wu, D., Du, H., Zhu, H., Chen, S., & Pan, H. (2022). Review on facial-recognition-based applications in disease diagnosis. Bioengineering, 9(7), 273. Search in Google Scholar

Britto, P. R., Lye, S. J., Proulx, K., Yousafzai, A. K., Matthews, S. G., Vaivada, T., ... & Bhutta, Z. A. (2017). Nurturing care: promoting early childhood development. The lancet, 389(10064), 91-102. Search in Google Scholar

Utesch, T., Bardid, F., Büsch, D., & Strauss, B. (2019). The relationship between motor competence and physical fitness from early childhood to early adulthood: a meta-analysis. Sports medicine, 49, 541-551. Search in Google Scholar

Zhang, Z., Zhao, L., & Yang, T. (2021, August). Research on the application of artificial intelligence in image recognition technology. In Journal of Physics: Conference Series (Vol. 1992, No. 3, p. 032118). IOP Publishing. Search in Google Scholar

Carson, V., Lee, E. Y., Hewitt, L., Jennings, C., Hunter, S., Kuzik, N., ... & Tremblay, M. S. (2017). Systematic review of the relationships between physical activity and health indicators in the early years (0-4 years). BMC public health, 17, 33-63. Search in Google Scholar

Daelmans, B., Darmstadt, G. L., Lombardi, J., Black, M. M., Britto, P. R., Lye, S., ... & Richter, L. M. (2017). Early childhood development: the foundation of sustainable development. The Lancet, 389(10064), 9-11. Search in Google Scholar

Dankiw, K. A., Tsiros, M. D., Baldock, K. L., & Kumar, S. (2020). The impacts of unstructured nature play on health in early childhood development: A systematic review. Plos one, 15(2), e0229006. Search in Google Scholar

World Health Organization. (2020). Improving early childhood development: WHO guideline. World Health Organization. Search in Google Scholar

Shunkang Ling,Nianyi Wang,Jingbin Li & Longpeng Ding.(2024).Accurate Recognition of Jujube Tree Trunks Based on Contrast Limited Adaptive Histogram Equalization Image Enhancement and Improved YOLOv8.Forests(4). Search in Google Scholar

Li Weiming & Jiang Xianyang.(2024).A novel evaluation standard combining gini-index and variation coefficient for double plateaus histogram equalization.Signal, Image and Video Processing(4),3321-3328. Search in Google Scholar

Ning Cao & Yupu Liu.(2024).High-Noise Grayscale Image Denoising Using an Improved Median Filter for the Adaptive Selection of a Threshold.Applied Sciences(2), Search in Google Scholar

Mingdong Zhou,Haojie Lian,Ole Sigmund & Niels Aage.(2018).Shape morphing and topology optimization of fluid channels by explicit boundary tracking.International Journal for Numerical Methods in Fluids(6),296-313. Search in Google Scholar