Jack Sim

2.5k total citations
12 papers, 710 citations indexed

About

Jack Sim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Jack Sim has authored 12 papers receiving a total of 710 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 1 paper in Information Systems. Recurrent topics in Jack Sim's work include Advanced Image and Video Retrieval Techniques (6 papers), Video Surveillance and Tracking Methods (3 papers) and Image Retrieval and Classification Techniques (3 papers). Jack Sim is often cited by papers focused on Advanced Image and Video Retrieval Techniques (6 papers), Video Surveillance and Tracking Methods (3 papers) and Image Retrieval and Classification Techniques (3 papers). Jack Sim collaborates with scholars based in United States, United Kingdom and South Korea. Jack Sim's co-authors include André Araujo, Tobias Weyand, Bohyung Han, Bingyi Cao, Hartwig Adam, Menglong Zhu, Marvin Teichmann, Jianbo Shi, Haifeng Gong and Maxim Likhachev and has published in prestigious journals such as Journal of Electronic Commerce in Organizations, Apollo (University of Cambridge) and arXiv (Cornell University).

In The Last Decade

Jack Sim

12 papers receiving 694 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jack Sim United States	7	480	158	92	61	45	12	710
Mohammadreza Babaee Germany	9	528 1.1×	124 0.8×	36 0.4×	194 3.2×	26 0.6×	18	637
Yiming Cui United States	14	547 1.1×	143 0.9×	109 1.2×	40 0.7×	58 1.3×	21	727
Jimin Yu China	13	311 0.6×	58 0.4×	90 1.0×	46 0.8×	27 0.6×	62	729
Monika Bansal India	5	295 0.6×	116 0.7×	57 0.6×	29 0.5×	26 0.6×	12	548
Jianfeng Li China	15	372 0.8×	131 0.8×	65 0.7×	53 0.9×	53 1.2×	74	788
Alexandre Sablayrolles France	5	437 0.9×	261 1.7×	42 0.5×	31 0.5×	55 1.2×	7	756
Amit Agrawal United States	6	849 1.8×	343 2.2×	63 0.7×	35 0.6×	30 0.7×	14	1.1k
Caixia Yan China	11	325 0.7×	241 1.5×	31 0.3×	64 1.0×	28 0.6×	20	556
Huiyuan Fu China	15	760 1.6×	196 1.2×	38 0.4×	127 2.1×	52 1.2×	55	1.0k

Countries citing papers authored by Jack Sim

Since Specialization

Citations

This map shows the geographic impact of Jack Sim'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 Jack Sim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jack Sim more than expected).

Fields of papers citing papers by Jack Sim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack Sim. 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 Jack Sim. The network helps show where Jack Sim may publish in the future.

Co-authorship network of co-authors of Jack Sim

This figure shows the co-authorship network connecting the top 25 collaborators of Jack Sim. A scholar is included among the top collaborators of Jack Sim 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 Jack Sim. Jack Sim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

1.

Xia, Fangting, et al.. (2021). Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food. 8899–8907. 70 indexed citations

2.

Weyand, Tobias, André Araujo, Bingyi Cao, & Jack Sim. (2020). Google Landmarks Dataset v2 – A Large-Scale Benchmark for Instance-Level Recognition and Retrieval. 2572–2581. 168 indexed citations

3.

Cao, Bingyi, André Araujo, & Jack Sim. (2020). Unifying Deep Local and Global Features for Efficient Image Search.. 5 indexed citations

4.

Teichmann, Marvin, André Araujo, Menglong Zhu, & Jack Sim. (2019). Detect-To-Retrieve: Efficient Regional Aggregation for Image Search. Apollo (University of Cambridge). 5104–5113. 76 indexed citations

5.

Sim, Jack, et al.. (2019). Computing Receptive Fields of Convolutional Neural Networks. 4(11). 192 indexed citations

6.

Pillai, Jay J., et al.. (2019). Bringing Vision to the Blind: From Coarse to Fine, One Dollar at a Time. 481–490. 3 indexed citations

7.

Han, Bohyung, Jack Sim, & Hartwig Adam. (2017). BranchOut: Regularization for Online Ensemble Tracking with Convolutional Neural Networks. 521–530. 100 indexed citations

8.

Han, Bohyung, Hartwig Adam, & Jack Sim. (2017). BranchOut: Regularization for Online Ensemble Tracking with CNNs. 1 indexed citations

9.

Noh, Hyeonwoo, André Araujo, Jack Sim, & Bohyung Han. (2016). Image Retrieval with Deep Local Features and Attention-based Keypoints.. arXiv (Cornell University). 6 indexed citations

10.

Gong, Haifeng, Jack Sim, Maxim Likhachev, & Jianbo Shi. (2011). Multi-hypothesis motion planning for visual object tracking. 619–626. 56 indexed citations

11.

Han, Bohyung, Jihun Hamm, & Jack Sim. (2011). Personalized video summarization with human in the loop. 51–57. 32 indexed citations

12.

Sim, Jack, et al.. (2010). Technology to Toilets. Journal of Electronic Commerce in Organizations. 8(3). 49–59. 1 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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