Ser Nam Lim

1.2k total citations
11 papers, 522 citations indexed

About

Ser Nam Lim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Ser Nam Lim has authored 11 papers receiving a total of 522 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 2 papers in Aerospace Engineering. Recurrent topics in Ser Nam Lim's work include Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Adversarial Robustness in Machine Learning (2 papers). Ser Nam Lim is often cited by papers focused on Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Adversarial Robustness in Machine Learning (2 papers). Ser Nam Lim collaborates with scholars based in United States, Israel and Australia. Ser Nam Lim's co-authors include Arpit Jain, Swami Sankaranarayanan, Rama Chellappa, Yogesh Balaji, Ming‐Ching Chang, Siwei Lyu, Wenbo Li, Longyin Wen, Xiao Bian and Ning Zhou and has published in prestigious journals such as International Journal of Molecular Sciences, arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Ser Nam Lim

11 papers receiving 501 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ser Nam Lim United States	6	403	266	66	59	47	11	522
Nouf Abdullah Almujally Saudi Arabia	14	237 0.6×	166 0.6×	80 1.2×	69 1.2×	38 0.8×	65	599
Hanli Zhao China	16	355 0.9×	190 0.7×	50 0.8×	31 0.5×	23 0.5×	54	646
Feifei Lee Japan	15	399 1.0×	174 0.7×	49 0.7×	21 0.4×	41 0.9×	70	619
Paolo Rota Italy	14	347 0.9×	295 1.1×	23 0.3×	67 1.1×	24 0.5×	34	613
Diego Ortego Spain	8	333 0.8×	400 1.5×	54 0.8×	28 0.5×	18 0.4×	14	635
Laura Sevilla-Lara United States	6	817 2.0×	313 1.2×	53 0.8×	69 1.2×	116 2.5×	13	919
Haibing Ren China	12	371 0.9×	113 0.4×	36 0.5×	26 0.4×	41 0.9×	29	457
Golnaz Ghiasi United States	10	512 1.3×	227 0.9×	54 0.8×	20 0.3×	17 0.4×	13	629
Kang Zheng United States	11	388 1.0×	178 0.7×	59 0.9×	119 2.0×	16 0.3×	24	586

Countries citing papers authored by Ser Nam Lim

Since Specialization

Citations

This map shows the geographic impact of Ser Nam Lim's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ser Nam Lim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ser Nam Lim more than expected).

Fields of papers citing papers by Ser Nam Lim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ser Nam Lim. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ser Nam Lim. The network helps show where Ser Nam Lim may publish in the future.

Co-authorship network of co-authors of Ser Nam Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Ser Nam Lim. A scholar is included among the top collaborators of Ser Nam Lim based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ser Nam Lim. Ser Nam Lim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Chen, Lin, et al.. (2021). A Continuous Mapping For Augmentation Design. Neural Information Processing Systems. 34. 1 indexed citations

2.

Lim, Ser Nam, et al.. (2021). Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods. arXiv (Cornell University). 29 indexed citations

3.

Lou, Aaron, et al.. (2020). Neural Manifold Ordinary Differential Equations. arXiv (Cornell University). 33. 17548–17558. 1 indexed citations

4.

Yi, Wei, Ming‐Ching Chang, Yiming Ying, Ser Nam Lim, & Siwei Lyu. (2018). Explain Black-box Image Classifications Using Superpixel-based Interpretation. 1640–1645. 4 indexed citations

5.

Sankaranarayanan, Swami, Yogesh Balaji, Arpit Jain, Ser Nam Lim, & Rama Chellappa. (2018). Learning from Synthetic Data: Addressing Domain Shift for Semantic Segmentation. 3752–3761. 284 indexed citations

6.

Li, Wenbo, Longyin Wen, Ming‐Ching Chang, Ser Nam Lim, & Siwei Lyu. (2017). Adaptive RNN Tree for Large-Scale Human Action Recognition. 1453–1461. 91 indexed citations

7.

Sankaranarayanan, Swami, Arpit Jain, & Ser Nam Lim. (2017). Guided Perturbations: Self-Corrective Behavior in Convolutional Neural Networks. abs 1405 312. 3582–3590. 2 indexed citations

8.

Uzunbaş, Mustafa Gökhan, et al.. (2017). A Reinforcement Learning Approach to the View Planning Problem. 5094–5102. 44 indexed citations

9.

Lim, Ser Nam, et al.. (2016). Tooth guard: A vision system for detecting missing tooth in rope mine shovel. 5 indexed citations

10.

Bian, Xiao, Ser Nam Lim, & Ning Zhou. (2016). Multiscale fully convolutional network with application to industrial inspection. 1–8. 49 indexed citations

11.

Lim, Ser Nam & Larry S. Davis. (2006). A One-Threshold Algorithm for Detecting Abandoned Packages Under Severe Occlusions Using a Single Camera. International Journal of Molecular Sciences. 16(7). 15425–41. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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