D.L. Swets

2.7k total citations · 1 hit paper
9 papers, 1.4k citations indexed

About

D.L. Swets is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, D.L. Swets has authored 9 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 3 papers in Media Technology. Recurrent topics in D.L. Swets's work include Image Retrieval and Classification Techniques (6 papers), Face and Expression Recognition (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). D.L. Swets is often cited by papers focused on Image Retrieval and Classification Techniques (6 papers), Face and Expression Recognition (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). D.L. Swets collaborates with scholars based in United States. D.L. Swets's co-authors include Juyang Weng, John Weng and Yuntao Cui and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Multimedia Tools and Applications and Proceedings - International Conference on Image Processing.

In The Last Decade

D.L. Swets

8 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Using discriminant eigenfeatures for image retrieval

1996 1.2k citations D.L. Swets, Juyang Weng IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
D.L. Swets United States	7	1.2k	313	244	229	98	9	1.4k
Gwo‐Jong Yu Taiwan	10	1.0k 0.9×	328 1.0×	207 0.8×	279 1.2×	104 1.1×	30	1.5k
Ja‐Chen Lin Taiwan	8	1.3k 1.1×	327 1.0×	224 0.9×	299 1.3×	105 1.1×	17	1.4k
Baozong Yuan China	12	866 0.7×	162 0.5×	148 0.6×	237 1.0×	69 0.7×	120	1.2k
Martin Lades Germany	6	1.4k 1.2×	468 1.5×	225 0.9×	215 0.9×	56 0.6×	13	1.7k
Baback Moghaddam United States	15	1.0k 0.9×	291 0.9×	110 0.5×	208 0.9×	38 0.4×	28	1.3k
Atalay Barkana Türkiye	10	546 0.5×	193 0.6×	115 0.5×	183 0.8×	51 0.5×	33	799
S.Z. Li China	15	1.3k 1.1×	290 0.9×	197 0.8×	180 0.8×	25 0.3×	31	1.5k
K. Etemad United States	8	753 0.7×	183 0.6×	140 0.6×	125 0.5×	43 0.4×	12	840
Ioan Buciu Romania	15	713 0.6×	151 0.5×	81 0.3×	189 0.8×	30 0.3×	37	952
Jan C. Vorbrüggen Germany	5	1.0k 0.9×	268 0.9×	171 0.7×	165 0.7×	19 0.2×	5	1.3k

Countries citing papers authored by D.L. Swets

Since Specialization

Citations

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

Fields of papers citing papers by D.L. Swets

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.L. Swets. 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 D.L. Swets. The network helps show where D.L. Swets may publish in the future.

Co-authorship network of co-authors of D.L. Swets

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

All Works

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9 of 9 papers shown

1.

Swets, D.L. & Juyang Weng. (2002). Efficient image retrieval using a network with complex neurons. 4. 1600–1605. 1 indexed citations

2.

Cui, Yuntao, D.L. Swets, & John Weng. (2002). Learning-based hand sign recognition using SHOSLIF-M. 631–636. 44 indexed citations

3.

Swets, D.L. & Juyang Weng. (2002). Discriminant analysis and eigenspace partition tree for face and object recognition from views. 192–197. 23 indexed citations

4.

Swets, D.L. & John Weng. (2002). Efficient content-based image retrieval using automatic feature selection. 85–90. 39 indexed citations

5.

Swets, D.L., et al.. (2002). Genetic algorithms for object recognition in a complex scene. Proceedings - International Conference on Image Processing. 2. 595–598. 35 indexed citations

6.

Swets, D.L. & Juyang Weng. (1999). Hierarchical discriminant analysis for image retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence. 21(5). 386–401. 69 indexed citations

7.

Swets, D.L., et al.. (1998). An Image Database System with Support for Traditional Alphanumeric Queries and Content-Based Queries by Example. Multimedia Tools and Applications. 7(3). 181–212. 6 indexed citations

8.

Swets, D.L. & Juyang Weng. (1996). Using discriminant eigenfeatures for image retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence. 18(8). 831–836. 1162 indexed citations breakdown →

9.

Swets, D.L.. (1996). The self-organizing hierarchical optimal subspace learning and inference framework for view-based object recognition and image retrieval. Michigan State University Libraries. 3 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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