338 publications in total across all disciplines
The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2027. The highlighted bar marks where Yap-Peng Tan sits on this spectrum.
This scientist: 307 publications — 75th percentile
75% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2027. The highlighted bar marks where Yap-Peng Tan sits on this spectrum.
This scientist: 58 D-Index — 75th percentile
75% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Yap-Peng Tan is affiliated with Nanyang Technological University in Singapore. Their research is primarily situated in the field of computer science, with a particular focus on computer vision and pattern recognition. Tan's work also spans artificial intelligence, media technology, safety, risk, reliability and quality, and radiology, nuclear medicine, and imaging.
Their scholarly output includes numerous recent papers across major venues, reflecting diverse topics within their field. Notable publications include:
Tan collaborates frequently with several co-authors, including:
The most frequent venues for Tan's publications include:
The main fields of study and research topics addressed in Tan's work cover:
In recognition of contributions to visual data analysis and processing, Yap-Peng Tan was awarded the IEEE Fellow distinction in 2019.
Junlin Hu;Jiwen Lu;Yap-Peng Tan
Jiwen Lu;Junlin Hu;Xiuzhuang Zhou;Yuanyuan Shang
Wenmiao Lu;Yap-Peng Tan
Jiwen Lu;Yap-Peng Tan;Gang Wang
Yap-Peng Tan;D.D. Saur;S.R. Kulkami;P.J. Ramadge
Junlin Hu;Jiwen Lu;Yap-Peng Tan
Junlin Hu;Jiwen Lu;Yap-Peng Tan;Jie Zhou
Jiwen Lu;Junlin Hu;Yap-Peng Tan
Nai-Xiang Lian;Lanlan Chang;Yap-Peng Tan;V. Zagorodnov
Junlin Hu;Jiwen Lu;Junsong Yuan;Yap-Peng Tan
Drew D. Saur;Yap-Peng Tan;Sanjeev R. Kulkarni;Peter J. Ramadge
Lanlan Chang;Yap-Peng Tan
Jiwen Lu;Yap-Peng Tan
Junlin Hu;Jiwen Lu;Yap-Peng Tan
Ji Tao;Mukherjee Turjo;Mun-Fei Wong;Mengdi Wang
Jiwen Lu;Yap-Peng Tan
Jingjing Meng;Hongxing Wang;Junsong Yuan;Yap-Peng Tan
Ci Wang;Lei Zhang;Yuwen He;Yap-Peng Tan
Yin Zhao;Zhenzhong Chen;Ce Zhu;Yap-Peng Tan
Renliang Weng;Jiwen Lu;Yap-Peng Tan
Jiwen Lu;Yap-Peng Tan;Gang Wang
If you think any of the details on this page are incorrect, let us know.
Exploring Computer Science in the USA opens doors to a variety of online degree options that can jumpstart your tech career. For those eager to quickly enter the workforce, consider programs that are among the fastest degree to get. These paths allow you to gain essential skills in less time, helping you begin earning sooner.
Artificial intelligence is a booming field, and there are increasingly accessible ai degree programs available online. These programs are ideal for those who want to specialize their expertise while managing costs.
When choosing your focus, it can help to look at the college programs that align with in-demand careers, such as software development, cybersecurity, or data science.
If advancing your education is a priority, many busy professionals opt for the easiest online master's degree options, balancing further study with work or family commitments. Selecting the right online pathway can maximize your career potential in computer science.
University of Minnesota
Intel (United States)
National Health Research Institutes
AgResearch
University of Michigan–Ann Arbor
University of Melbourne
University of Sydney
University of Salento
University of California, Los Angeles
King's College London
University of Milano-Bicocca
Karolinska Institute
Paul Sabatier University
Bangor University
University of Poitiers
École Normale Supérieure Paris-Saclay
