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Sun Wen's resume (education and work experience)
Sun Wen, female, born in 1985, Ph.D., is currently a professor in a university. Mainly engaged in computer vision, machine learning, artificial intelligence and other research work He has published more than 30 papers in academic journals and conferences at home and abroad, including many top conference papers. He has won many academic awards such as XX Award and XX Award.

academic degree

From 2003 to 2007, I studied computer science and technology in XX University and got a bachelor's degree.

From 2007 to 2065438+00, he studied computer science and technology in XX University and obtained a master's degree.

20 10-20 13 studied computer science and technology in XX university and obtained a doctorate.

Business experience

20 13-20 15, lecturer of computer science and technology department of XX university.

20 15- Up to now, he has served as an associate professor and professor in the Department of Computer Science and Technology of XX University.

During his work, Sun Wen took an active part in various academic activities, including being a reviewer of many international conferences and periodicals, organizing invited speeches at international conferences, and being the head of many national and provincial scientific research projects.

Computer vision research

Sun Wen's research in the field of computer vision covers image processing, target detection, face recognition, behavior recognition and many other aspects. Among them, her research achievements in the field of target detection have attracted wide attention from colleagues at home and abroad.

The following are the research results of Sun Wen in the field of target detection:

1. Object detection algorithm based on deep learning

The algorithm uses deep convolution neural network to extract features, and combines with regional prediction network to detect targets. The algorithm is tested on several public data sets, and the results show that its detection accuracy and speed are better than the traditional target detection algorithm.

2. Multi-scale target detection algorithm

The algorithm can detect targets with different scales by scaling the image several times. The algorithm performs well when dealing with large-scale changing images.