Joseph Luttrell

940 total citations
17 papers, 523 citations indexed

About

Joseph Luttrell is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Joseph Luttrell has authored 17 papers receiving a total of 523 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Molecular Biology and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Joseph Luttrell's work include Computational Drug Discovery Methods (4 papers), Automated Road and Building Extraction (2 papers) and Protein Structure and Dynamics (2 papers). Joseph Luttrell is often cited by papers focused on Computational Drug Discovery Methods (4 papers), Automated Road and Building Extraction (2 papers) and Protein Structure and Dynamics (2 papers). Joseph Luttrell collaborates with scholars based in United States and China. Joseph Luttrell's co-authors include Chaoyang Zhang, Juanying Xie, Ran Liu, Ping Gong, Zhaoxian Zhou, Gabriel Idakwo, Huixiao Hong, Minjun Chen, Chaoyang Zhang and Meng Song and has published in prestigious journals such as Sensors, BMC Bioinformatics and Experimental Biology and Medicine.

In The Last Decade

Joseph Luttrell

15 papers receiving 507 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joseph Luttrell United States 9 212 157 153 138 109 17 523
Zerrin Işık Türkiye 10 135 0.6× 150 1.0× 71 0.5× 69 0.5× 120 1.1× 32 410
Zihan Guo China 12 132 0.6× 283 1.8× 29 0.2× 114 0.8× 104 1.0× 39 549
Giovanna Maria Dimitri Italy 12 94 0.4× 81 0.5× 34 0.2× 51 0.4× 55 0.5× 42 374
Jiansheng Wu China 11 98 0.5× 261 1.7× 27 0.2× 156 1.1× 73 0.7× 39 525
Tomasz Arodź United States 12 72 0.3× 247 1.6× 42 0.3× 220 1.6× 57 0.5× 27 601
Ladislav Rampášek Canada 6 71 0.3× 257 1.6× 50 0.3× 153 1.1× 22 0.2× 8 532
Jiahua Rao China 10 131 0.6× 434 2.8× 40 0.3× 256 1.9× 24 0.2× 24 641
Jianbo Fu China 17 90 0.4× 806 5.1× 53 0.3× 223 1.6× 19 0.2× 28 1.2k
Maha A. Thafar Saudi Arabia 12 73 0.3× 465 3.0× 61 0.4× 297 2.2× 16 0.1× 29 700

Countries citing papers authored by Joseph Luttrell

Since Specialization
Citations

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

Fields of papers citing papers by Joseph Luttrell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joseph Luttrell

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

All Works

17 of 17 papers shown
1.
2.
Wang, Mingzhao, Ran Liu, Joseph Luttrell, Chaoyang Zhang, & Juanying Xie. (2025). Detection of Masses in Mammogram Images Based on the Enhanced RetinaNet Network With INbreast Dataset. Journal of Multidisciplinary Healthcare. Volume 18. 675–695. 2 indexed citations
3.
Luttrell, Joseph, Yuanyuan Zhang, & Chaoyang Zhang. (2024). Automatically detect crosswalks from satellite view images: A deep learning approach with ground truth verification. International Journal of Transportation Science and Technology. 16. 165–176. 1 indexed citations
4.
5.
Zhang, Yuanyuan, Joseph Luttrell, & Chaoyang Zhang. (2024). How to detect occluded crosswalks in overview images? Comparing three methods in a heavily occluded area. International Journal of Transportation Science and Technology. 17. 148–160.
6.
Yang, Bei, et al.. (2023). A quantum-based oversampling method for classification of highly imbalanced and overlapped data. Experimental Biology and Medicine. 248(24). 2500–2513. 1 indexed citations
7.
Song, Meng, Jonathan Greenbaum, Joseph Luttrell, et al.. (2022). An autoencoder-based deep learning method for genotype imputation. Frontiers in Artificial Intelligence. 5. 1028978–1028978. 8 indexed citations
8.
Idakwo, Gabriel, Joseph Luttrell, Yan Li, et al.. (2020). Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets. Journal of Cheminformatics. 12(1). 66–66. 55 indexed citations
9.
Song, Meng, Jonathan Greenbaum, Joseph Luttrell, et al.. (2020). A Review of Integrative Imputation for Multi-Omics Datasets. Frontiers in Genetics. 11. 570255–570255. 78 indexed citations
10.
Luttrell, Joseph, Tong Liu, Chaoyang Zhang, & Zheng Wang. (2019). Predicting protein residue-residue contacts using random forests and deep networks. BMC Bioinformatics. 20(S2). 100–100. 10 indexed citations
11.
Xie, Juanying, Ran Liu, Joseph Luttrell, & Chaoyang Zhang. (2019). Deep Learning Based Analysis of Histopathological Images of Breast Cancer. Frontiers in Genetics. 10. 80–80. 190 indexed citations
12.
13.
Idakwo, Gabriel, Joseph Luttrell, Minjun Chen, et al.. (2019). A Review of Feature Reduction Methods for QSAR-Based Toxicity Prediction. Aquila Digital Community (University of Southern Mississippi). 119–139. 15 indexed citations
14.
Luttrell, Joseph, Zhaoxian Zhou, Chaoyang Zhang, et al.. (2018). A deep transfer learning approach to fine-tuning facial recognition models. Aquila Digital Community (University of Southern Mississippi). 14 indexed citations
15.
Idakwo, Gabriel, Joseph Luttrell, Minjun Chen, et al.. (2018). A review on machine learning methods forin silicotoxicity prediction. Journal of Environmental Science and Health Part C. 36(4). 169–191. 98 indexed citations
16.
Luttrell, Joseph, et al.. (2017). Facial Recognition via Transfer Learning: Fine-Tuning Keras_vggface. Aquila Digital Community (University of Southern Mississippi). 576–579. 8 indexed citations
17.
Wang, Juexin, Joseph Luttrell, Ning Zhang, et al.. (2016). Exploring Human Diseases and Biological Mechanisms by Protein Structure Prediction and Modeling. Advances in experimental medicine and biology. 939. 39–61. 8 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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