Zhang, K. (2025). Develop a novel deep learning-based framework using convolutional neural networks for real-time object detection and tracking in embedded systems. Journal of Computational Methods in Sciences & Engineering, 25(6), 5616-5632. https://doi.org/10.1177/14727978251346034

ZHANG, Kai, 2025. Develop a novel deep learning-based framework using convolutional neural networks for real-time object detection and tracking in embedded systems. Journal of Computational Methods in Sciences & Engineering. 1 November 2025. Vol. 25, no. 6, p. 5616-5632. DOI 10.1177/14727978251346034.

Zhang, K. „Develop a Novel Deep Learning-Based Framework Using Convolutional Neural Networks for Real-Time Object Detection and Tracking in Embedded Systems.“. Journal of Computational Methods in Sciences & Engineering, Bd. 25, Nr. 6, November 2025, S. 5616-32, https://doi.org/10.1177/14727978251346034.

Zhang, Kai: Develop a novel deep learning-based framework using convolutional neural networks for real-time object detection and tracking in embedded systems., Journal of Computational Methods in Sciences & Engineering 2025, 5616-5632.

Zhang, K. (2025), „Develop a novel deep learning-based framework using convolutional neural networks for real-time object detection and tracking in embedded systems.“, Journal of Computational Methods in Sciences & Engineering, Vol. 25 No. 6, S. 5616-5632.