Author:
Ahmed Md Foysal,He Gang,Wang Sikai
Funder
Sichuan Science and Technology Program
NHC Key Laboratory of Nuclear Technology Medical Transformation
Publisher
Springer Science and Business Media LLC
Reference34 articles.
1. Kumar, P., Chauhan, S., Awasthi, L.K.: Human Activity Recognition (HAR) Using Deep Learning: Review, Methodologies, Progress and Future Research Directions. Arch. Comput. Methods Eng. 31(1), 179–219 (2024)
2. Silva, V., Soares, F., Esteves, J.S., Vercelli, G.: Human action recognition using an image-based temporal and spatial representation. In: 12th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), pp. 41–46 (2020)
3. Konak, O., Wischmann, A., De Water, R., Arnrich, B.: A Real-time Human Pose Estimation Approach for Optimal Sensor Placement in Sensor-based Human Activity Recognition. In: Proceedings of the 8th International Workshop on Sensor-Based Activity Recognition and Artificial Intelligence, pp. 1–6 (2023)
4. Camarena, F., Gonzalez-Mendoza, M., Chang, L., Cuevas-Ascencio, R.: An Overview of the Vision-Based Human Action Recognition Field. Math. Comput. Appl. 28(2), 61 (2023)
5. Beddiar, D.R., Nini, B., Sabokrou, M., Hadid, A.: Vision-based human activity recognition: a survey. Multi. Tools Appl. 79(41), 30509–30555 (2020)