Stephen Rawls

818 total citations
14 papers, 408 citations indexed

About

Stephen Rawls is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Stephen Rawls has authored 14 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Signal Processing. Recurrent topics in Stephen Rawls's work include Handwritten Text Recognition Techniques (7 papers), Multimodal Machine Learning Applications (4 papers) and Face recognition and analysis (4 papers). Stephen Rawls is often cited by papers focused on Handwritten Text Recognition Techniques (7 papers), Multimodal Machine Learning Applications (4 papers) and Face recognition and analysis (4 papers). Stephen Rawls collaborates with scholars based in United States, Israel and Germany. Stephen Rawls's co-authors include Prem Natarajan, Gérard Medioni, Iacopo Masi, Yue Wu, Wael AbdAlmageed, Tal Hassner, Shai Har-El, Jongmoo Choi, Ram Nevatia and Jungyeon Kim and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence and IRIS Research product catalog (Sapienza University of Rome).

In The Last Decade

Stephen Rawls

14 papers receiving 386 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Stephen Rawls United States	8	371	168	62	17	16	14	408
Minyoung Kim South Korea	5	309 0.8×	62 0.4×	57 0.9×	33 1.9×	36 2.3×	9	359
Cameron Whitelam United States	5	301 0.8×	185 1.1×	33 0.5×	11 0.6×	8 0.5×	7	331
Vijay Kumar Sharma India	8	240 0.6×	49 0.3×	46 0.7×	4 0.2×	28 1.8×	24	288
Seyoon Jeong South Korea	11	297 0.8×	187 1.1×	34 0.5×	23 1.4×	29 1.8×	66	369
Yake Wei China	5	140 0.4×	83 0.5×	118 1.9×	7 0.4×	10 0.6×	8	271
Amirhossein Habibian Netherlands	12	464 1.3×	90 0.5×	140 2.3×	13 0.8×	13 0.8×	19	504
K. Jonsson United Kingdom	6	252 0.7×	158 0.9×	75 1.2×	5 0.3×	21 1.3×	7	332
Lie Gu United States	7	290 0.8×	56 0.3×	30 0.5×	28 1.6×	11 0.7×	7	319
Etienne Marcheret United States	8	106 0.3×	208 1.2×	150 2.4×	20 1.2×	5 0.3×	28	304
Shuai Nie China	12	149 0.4×	171 1.0×	176 2.8×	47 2.8×	28 1.8×	25	346

Countries citing papers authored by Stephen Rawls

Since Specialization

Citations

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

Fields of papers citing papers by Stephen Rawls

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Rawls

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Rawls. A scholar is included among the top collaborators of Stephen Rawls 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 Stephen Rawls. Stephen Rawls 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:

14 of 14 papers shown

1.

Dave, Achal, et al.. (2023). Visual Item Selection With Voice Assistants. 500–507. 1 indexed citations

2.

Chang, Ching-Yun, et al.. (2023). Translation-Enhanced Multilingual Text-to-Image Generation. 9174–9193. 2 indexed citations

3.

Zhu, Qile, Haidar Khan, Saleh Soltan, Stephen Rawls, & Wael Hamza. (2020). Don’t Parse, Insert: Multilingual Semantic Parsing with Insertion Based Decoding. 496–506. 16 indexed citations

4.

Rawls, Stephen, et al.. (2019). A Synthetic Recipe for OCR. 864–869. 10 indexed citations

5.

Masi, Iacopo, Feng-Ju Chang, Jongmoo Choi, et al.. (2018). Learning Pose-Aware Models for Pose-Invariant Face Recognition in the Wild. IEEE Transactions on Pattern Analysis and Machine Intelligence. 41(2). 379–393. 66 indexed citations

6.

Rawls, Stephen, et al.. (2018). How To Efficiently Increase Resolution in Neural OCR Models. 5. 140–144. 4 indexed citations

7.

Rawls, Stephen, et al.. (2017). Combining Convolutional Neural Networks and LSTMs for Segmentation-Free OCR. 155–160. 17 indexed citations

8.

Cao, Huaigu, Stephen Rawls, & Prem Natarajan. (2017). 1990 US Census Form Recognition Using CTC Network, WFST Language Model, and Surname Correction. 31. 977–982. 2 indexed citations

9.

Rawls, Stephen, Huaigu Cao, Ekraam Sabir, & Prem Natarajan. (2017). Combining deep learning and language modeling for segmentation-free OCR from raw pixels. 119–123. 8 indexed citations

10.

Wu, Yue, Prem Natarajan, Stephen Rawls, & Wael AbdAlmageed. (2016). Learning document image binarization from data. 3763–3767. 21 indexed citations

11.

Wu, Yue, et al.. (2016). Computationally efficient template-based face recognition. 9. 1424–1429. 2 indexed citations

12.

Masi, Iacopo, Stephen Rawls, Gérard Medioni, & Prem Natarajan. (2016). Pose-Aware Face Recognition in the Wild. 4838–4846. 166 indexed citations

13.

AbdAlmageed, Wael, Yue Wu, Stephen Rawls, et al.. (2016). Face recognition using deep multi-pose representations. IRIS Research product catalog (Sapienza University of Rome). 1–9. 92 indexed citations

14.

Prasad, Rohit, et al.. (2010). The BBN document analysis service. 447–454. 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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