Publications by authors named "Chengang Dong"

Image super-resolution (SR) is a formidable challenge due to the intricacies of the underwater environment such as light absorption, scattering, and color distortion. Plenty of deep learning methods have provided a substantial performance boost for SR. Nevertheless, these methods are not only computationally expensive but also often lack flexibility in adapting to severely degraded image statistics.

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The objective of human pose estimation (HPE) derived from deep learning aims to accurately estimate and predict the human body posture in images or videos via the utilization of deep neural networks. However, the accuracy of real-time HPE tasks is still to be improved due to factors such as partial occlusion of body parts and limited receptive field of the model. To alleviate the accuracy loss caused by these issues, this paper proposes a real-time HPE model called based on the YOLOv8 framework.

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Terahertz (THz) waves have unique advantages in detecting biological substances. However, due to the strong absorption of THz waves by water, the development of THz detection technology in this field is seriously restricted. At present, although there are a few methods to detect hydrated materials, they cannot be widely used because of their defects.

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The photonic energy of terahertz wave is in the same order of magnitude as the rotational and vibrational energy levels of organic and biological macromolecules, so it has unique advantages in detecting cells and biological macromolecules. However, in the life environment, the dynamic time scale of cell-environment interaction and structural conformation change of biological macromolecules are within picosecond to millisecond, and water has strong absorption to terahertz wave, which has become the bottleneck problem for the detection of cells and biological macromolecules by terahertz technology. In this article, we developed a set of terahertz single measurement system based on the tilt wave front of grating pulse technique.

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