BAI Hua
Professor and Doctor
Tel.:+86-22-83955690
E-mail: baihua@tiangong.edu.cn
Introduction
Dr. BAI Hua was born in September 1980. He graduated with a Bachelor of Science degree in Electronic Information Science and Technology from Nankai University in 2003, and obtained a Master of Engineering degree in Optical Engineering from Nankai University in 2007. In 2011, he completed his Ph.D. in Optical Engineering from Nankai University. Since July 2011, he has been employed at Tiangong University, engaging in teaching and research. Currently, he is a professor and master's supervisor at Tiangong University.
Research areas
Dr. BAI Hua has been engaged in long-term research on optoelectronic detection technology and intelligent information processing technology, and has developed high-performance optoelectronic detection equipment such as ultraviolet, visible, and near-infrared ultra-weak photon detection systems, multi-channel ultrasound signal acquisition systems, and high-sensitivity spectral detection and analysis systems. He has led and participated in multiple projects funded by the National Natural Science Foundation of China and the Tianjin Natural Science Foundation, and has achieved a series of results in the integrated design of optics, mechanics, electronics, and algorithms, as well as system software and hardware development. He has published more than 50 academic papers, obtained over 20 authorized patents and software copyrights, and a paper he authored as the first author was awarded as one of the "Top 100 International Academic Papers with the Most Impact in China in 2011".
Main courses taught
Sensor and Detection Technology
Circuits and Systems
Main publications
Accurate segmentation algorithm of acoustic neuroma in the cerebellopontine angle based on ACP-TransUNet. Frontiers in Neuroscience, 2023, 17: 1207149
A novel deep learning model for medical image segmentation with Convolutional Neural Network and Transformer. Interdisciplinary Sciences: Computational Life Sciences, 2023, 15(4): 663~ 677
Blood cell counting based on U-Net++ and YOLOv5. Optoelectronics Letters, 2023, 19(6): 370 ~ 376
An improved U-Net for cell confluence estimation. Optoelectronics Letters, 2022, 18(6): 378 ~ 384
Spectral analysis of photo-induced delayed luminescence from mesenchymal stem cells for label-free cell viability assessment. Optoelectronics Letters, 2021, 17(6): 373 ~ 378
Chromosome Extraction Basedon U-Net and YOLOv3. IEEE Access, 2020, 8: 178563 ~ 178569
Label-free assessment of replicative senescence in mesenchymal stem cells by Raman microspectroscopy. Biomedical Optics Express, 2015, 6(11): 4493 ~ 4500
Detecting viability transitions of umbilical cord mesenchymal stem cells by Raman micro-spectroscopy, Laser Physics Letters, 2011, 8(1): 78 ~ 84
