The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Lai-Man Po sits on this spectrum.
This scientist: 226 publications — 55th percentile
55% 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 2026. The highlighted bar marks where Lai-Man Po sits on this spectrum.
This scientist: 38 D-Index — 30th percentile
30% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Lai-Man Po is affiliated with the City University of Hong Kong in China and has made significant contributions primarily in the field of Computer Science. The research output reflects a strong focus on Computer Vision and Pattern Recognition, which accounts for the majority of their publications. Other notable subfields include Artificial Intelligence, Signal Processing, Media Technology, and Genetics.
The scientist's research topics cover a variety of advanced areas within image and signal processing as well as machine learning techniques. Key topics of their work include:
Lai-Man Po has published extensively in several scientific venues, with a significant number of papers appearing in:
Their recent published works demonstrate engagement with topics like large kernel attention mechanisms in convolutional neural networks, GAN-based colorization techniques, and feature learning for biometric recognition. Some notable recent papers include:
The scientist collaborates regularly with several researchers in their field. Frequent coauthors include:
Lai-Man Po's body of work contributes to developments in neural networks and generative adversarial network applications, especially within advanced image and video processing tasks. Their research intersects with cutting-edge approaches to image synthesis, domain adaptation, and feature learning, reflecting a multidisciplinary approach within computer science and engineering domains.
Lai-Man Po;Wing-Chung Ma
Chun-Ho Cheung;Lai-Man Po
Chun-Ho Cheung;Lai-Man Po
Unknown
Litong Feng;Lai-Man Po;Yuming Li;Xuyuan Xu
Chun-Ho Cheung;Lai-Man Po
Chok-Kwan Cheung;Lai-Man Po
Ce Zhu;Xiao Lin;L. Chau;Lai-Man Po
Guan-Hao Chen;Chun-Ling Yang;Lai-Man Po;Sheng-Li Xie
Litong Feng;Lai-Man Po;Xuyuan Xu;Yuming Li
Yuzhi Zhao;Lai-Man Po;Qiong Yan;Wei Liu
Jie-Bin Xu;Lai-Man Po;Chok-Kwan Cheung
Mengyang Liu;Lai-Man Po;Hong Fu
Yuming Li;Lai-Man Po;Chun-Ho Cheung;Xuyuan Xu
Chun-Ho Cheung;Lai-Man Po
Chun-Ling Yang;Lai-Man Po;Wing-Hong Lam
Yasar Abbas Ur Rehman;Lai Man Po;Mengyang Liu
Ka-Man Wong;Kwok-Wai Cheung;Lai-Man Po
Yuming Li;Lai-Man Po;Xuyuan Xu;Litong Feng
Chi-Wai Lam;Lai-Man Po;Chun Ho Cheung
Lai-Man Po;Ka-Ho Ng;Kwok-Wai Cheung;Ka-Man Wong
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