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All issues Volume 491 (2024) E3S Web Conf., 491 (2024) 03024 References
Open Access
Issue
E3S Web Conf.
Volume 491, 2024
International Conference on Environmental Development Using Computer Science (ICECS’24)
Article Number 03024
Number of page(s) 10
Section Health Development
DOI https://doi.org/10.1051/e3sconf/202449103024
Published online 21 February 2024
  1. Ahad, Md Atiqur Rahman, Upal Mahbub, and Tauhidur Rahman. (2021). 9 of 14 Contactless Human Activity Analysis. Springer Nature. [CrossRef] [Google Scholar]
  2. Bi, Haixia, Miquel Perello-Nieto, Raul Santos-Rodriguez, and Peter Flach. (2021). “Human Activity Recognition Based on Dynamic Active Learning.” IEEE Journal of Biomedical and Health Informatics 25 (4): 922–34. [CrossRef] [PubMed] [Google Scholar]
  3. Chen, Kaixuan, Lina Yao, Dalin Zhang, Xianzhi Wang, Xiaojun Chang, and Feiping Nie. (2020). “A Semisupervised Recurrent Convolutional Attention Model for Human Activity Recognition.” IEEE Transactions on Neural Networks and Learning Systems 31 (5): 1747–56. [CrossRef] [PubMed] [Google Scholar]
  4. Deze, Zeng, Huan Huang, Rui Hou, Seungmin Rho, and Naveen Chilamkurti. (2021). Big Data Technologies and Applications: 10th EAI International Conference, BDTA 2020, and 13th EAI International Conference on Wireless Internet, WiCON 2020, Virtual Event, December 11, 2020, Proceedings. Springer Nature. [Google Scholar]
  5. Ferrari, Anna, Daniela Micucci, Marco Mobilio, and Paolo Napoletano. (2020). “On the Personalization of Classification Models for Human Activity Recognition.” IEEE Access 8: 32066–79. [CrossRef] [Google Scholar]
  6. Hilbe, Joseph M. (2016). Practical Guide to Logistic Regression. CRC Press. [CrossRef] [Google Scholar]
  7. Kong, Yu, and Yun Fu. 2016. “Action Recognition and Human Interaction.” Human Activity Recognition and Prediction. https://doi.org/10.1007/978-3-319-27004-3_2. [Google Scholar]
  8. Li, Ming, Zewei Shao, Zhongshao Li, Dandan Zhu, Junwei Wang, Smagul Zh Karazhanov, Ping Jin, and Xun Cao. (2023) “Co-Sputtering Crystal Lattice Selection for Rare Earth Metal-Based Multi Cation and Mixed Anion Photochromic Films.” Nanomaterials (Basel, Switzerland) 13 (4). https://doi.org/10.3390/nano13040684. [PubMed] [Google Scholar]
  9. Munoz-Organero, Mario. (2019). “Outlier Detection in Wearable Sensor Data for Human Activity Recognition (HAR) Based on DRNNs.” IEEE Access 7: 74422–36. [CrossRef] [Google Scholar]
  10. Omlor, Nicola, Maike Richter, Janik Goltermann, Lavinia A. Steinmann, Anna Kraus, Tiana Borgers, Melissa Klug, et al. (2023). “Treatment with the Second- Generation Antipsychotic Quetiapine Is Associated with Increased Subgenual ACC Activation during Reward Processing in Major Depressive Disorder.” Journal of Affective Disorders, February. https://doi.org/10.1016/j.jad.2023.02.102. [Google Scholar]
  11. Popescu, Ana-Cosmina, Irina Mocanu, and Bogdan Cramariuc. (2020). “Fusion Mechanisms for Human Activity Recognition Using Automated Machine Learning.” IEEE Access 8: 143996–14. [CrossRef] [Google Scholar]
  12. Qiu, Ye, An-Lin Liu, Jie Huang, Wen Zeng, Zhen-Ming Yang, Gao-Neng Fang, Ya Li, et al. (2023). “Comparison of the Clinical Features of HIV-Positive and HIV-Negative Hosts Infected with Talaromyces Marneffei: A Multicenter Retrospective Study.” International Journal of Infectious Diseases: IJID: Official Publication of the International Society for Infectious Diseases, April. https://doi.org/10.1016/j.ijid.2023.04.398. [Google Scholar]
  13. Ramanujam, E., Thinagaran Perumal, and S. Padmavathi. (2021). “Human Activity Recognition With Smartphone and Wearable Sensors Using Deep Learning Techniques: A Review.” IEEE Sensors Journal 21 (12): 13029–40. [CrossRef] [Google Scholar]
  14. Rico, Janaina, Larissa Siriani, Mila Wander, and Thati Machado. (2017). Princesas GPOWER. Qualis Editora e Comércio de Livros LTDA - ME. [Google Scholar]
  15. Sepahvand, Majid, and Fardin Abdali-Mohammadi. (2022). “Joint Learning Method with Teacher-Student Knowledge Distillation for on-Device Breast 10 of 14 Cancer Image Classification.” Computers in Biology and Medicine 155 (December): 106476. [Google Scholar]
  16. Sultan, Ali Bin Mazhar, Saqib Mehmood, and Hamza Zahid. (2022). “Man in the Middle Attack Detection for MQTT Based IoT Devices Using Different Machine Learning Algorithms.” In 2022 2nd International Conference on Artificial Intelligence (ICAI), 118–21. [Google Scholar]
  17. Zhang, Jianxin, Ming Yin, Deming Shu, and Dianzhi Liu. (2022). “The Establishment of the General Micro Expression Recognition Ability and Its Relevant Brain Activity.” Frontiers in Human Neuroscience 16 (December): 894702. [CrossRef] [PubMed] [Google Scholar]
  18. Zhang, Xiao, Hongzheng Yu, Yang Yang, Jingjing Gu, Yujun Li, Fuzhen Zhuang, Dongxiao Yu, and Zhaochun Ren. (2022). “HarMI: Human Activity Recognition Via Multi-Modality Incremental Learning.” IEEE Journal of Biomedical and Health Informatics 26 (3): 939–51. [CrossRef] [PubMed] [Google Scholar]

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