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33 results on '"Jin Zheng"'

18. INTRODUCTION

Author

Huang, Jun-Rong, primary, Zhuang, Hai-Ning, additional, and Jin, Zheng-Yu, additional

Published
2013
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32. Expression of Human Papillomavirus Type 16 L1 in Baculovirus Expression Systems.

Author

Walker, John M., Smales, C. Mark, James, David C., Jin Zheng, Lusheng Si, and Yili Wang

Abstract

With the great achievements of recombinant DNA technology, a variety of expression systems, including yeast, baculovirus, adenovirus, and attenuated Salmonella expression systems, have been used for the overexpression of recombinant proteins. Recombinant baculovirus-insect cell systems have become widely used because: (1) baculoviruses have a restricted host range, which is limited to specific invertebrate species. It is much safer to work with these viruses than most mammalian viruses. (2) Baculovirus has a large genome that accommodates large exogenous genes. Recombinant baculovirus can still propagate in insect cell lines or larvae from different insect species. (3) Recombinant proteins expressed by baculovirus are processed, modified, and targeted to their appropriate cellular locations, where they are functionally similar to their authentic counterparts. [ABSTRACT FROM AUTHOR]

Published
2005
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33. Fast Motion Detection Based on Accumulative Optical Flow and Double Background Model.

Author

Yue Hao, Jiming Liu, Yu-Ping Wang, Yiu-ming Cheung, Hujun Yin, Licheng Jiao, Jianfeng Ma, Yong-Chang Jiao, Jin Zheng, Bo Li, Bing Zhou, and Wei Li

Abstract

Optical flow and background subtraction are important methods for detecting motion in video sequences. This paper integrates the advantages of these two methods. Firstly, proposes a high precise algorithm for optical flow computation with analytic wavelet and M-estimator to solve the optical flow restricted equations. Secondly, introduces the extended accumulative optical flow and also provides its computational strategies, then obtains a robust motion detection algorithm. Furthermore, combines a background subtraction algorithm based on the double background model with the extended accumulative optical flow to give an abnormity alarm in time. All obvious proofs of experiments show that, our algorithm can precisely detect moving objects, no matter slow or little, preferably solve the occlusions as well as give an alarm fast. [ABSTRACT FROM AUTHOR]

Published
2005
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