Kyle Feuz

741 total citations · 1 hit paper
13 papers, 556 citations indexed

About

Kyle Feuz is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Surgery. According to data from OpenAlex, Kyle Feuz has authored 13 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 2 papers in Surgery. Recurrent topics in Kyle Feuz's work include Context-Aware Activity Recognition Systems (5 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Human-Automation Interaction and Safety (2 papers). Kyle Feuz is often cited by papers focused on Context-Aware Activity Recognition Systems (5 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Human-Automation Interaction and Safety (2 papers). Kyle Feuz collaborates with scholars based in United States. Kyle Feuz's co-authors include Diane J. Cook, Narayanan C. Krishnan, Maureen Schmitter‐Edgecombe, Robert Ball, Myriah D. Johnson, Daniel W. Cook and Miles E. Theurer and has published in prestigious journals such as Archives of Clinical Neuropsychology, Knowledge and Information Systems and ACM Transactions on Intelligent Systems and Technology.

In The Last Decade

Kyle Feuz

12 papers receiving 540 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.

Transfer learning for activity recognition: a survey

2013 335 citations Diane J. Cook, Kyle Feuz et al. Knowledge and Information Systems profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kyle Feuz United States	8	347	260	89	81	56	13	556
Thor Siiger Prentow Denmark	8	376 1.1×	245 0.9×	151 1.7×	183 2.3×	77 1.4×	12	665
Niall Twomey United Kingdom	11	280 0.8×	109 0.4×	154 1.7×	86 1.1×	114 2.0×	39	517
Lorena Qendro United Kingdom	6	331 1.0×	193 0.7×	207 2.3×	163 2.0×	27 0.5×	12	588
Marc Kurz Austria	8	581 1.7×	232 0.9×	190 2.1×	78 1.0×	158 2.8×	29	720
Maria E. Niessen Netherlands	7	223 0.6×	176 0.7×	67 0.8×	72 0.9×	70 1.3×	16	535
Labiba Gillani Fahad Pakistan	12	258 0.7×	126 0.5×	144 1.6×	94 1.2×	42 0.8×	28	479
Carlos Ruiz United States	12	129 0.4×	97 0.4×	76 0.9×	97 1.2×	67 1.2×	42	403
Bo-Jhang Ho United States	9	161 0.5×	469 1.8×	101 1.1×	130 1.6×	42 0.8×	15	777
Valentin Radu United Kingdom	11	362 1.0×	223 0.9×	133 1.5×	287 3.5×	84 1.5×	30	724
Carlos V. Regueiro Spain	15	196 0.6×	224 0.9×	77 0.9×	106 1.3×	55 1.0×	44	566

Countries citing papers authored by Kyle Feuz

Since Specialization

Citations

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

Fields of papers citing papers by Kyle Feuz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kyle Feuz

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

All Works

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13 of 13 papers shown

1.

Feuz, Kyle, et al.. (2022). Scalability and robustness of feed yard mortality prediction modeling to improve profitability. Agricultural and Resource Economics Review. 51(3). 610–632. 2 indexed citations

2.

Feuz, Kyle. (2021). Pedestrian Leadership and Egress Assistance Simulation Environment (PLEASE). Digital Commons - USU (Utah State University).

3.

Feuz, Kyle, et al.. (2020). Improving Feedlot Profitability Using Operational Data in Mortality Prediction Modeling. Journal of agricultural and resource economics. 46(2). 242–255. 3 indexed citations

4.

Ball, Robert, et al.. (2019). Applying Machine Learning to Improve Curriculum Design. 787–793. 14 indexed citations

5.

Feuz, Kyle & Diane J. Cook. (2017). Collegial activity learning between heterogeneous sensors. Knowledge and Information Systems. 53(2). 337–364. 33 indexed citations

6.

Feuz, Kyle & Diane J. Cook. (2017). Modeling Skewed Class Distributions by Reshaping the Concept Space. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 13 indexed citations

7.

Feuz, Kyle, et al.. (2015). Prompting technologies: A comparison of time-based and context-aware transition-based prompting. Technology and Health Care. 23(6). 745–756. 14 indexed citations

8.

Feuz, Kyle & Diane J. Cook. (2015). Transfer Learning across Feature-Rich Heterogeneous Feature Spaces via Feature-Space Remapping (FSR). ACM Transactions on Intelligent Systems and Technology. 6(1). 1–27. 64 indexed citations

9.

Feuz, Kyle, et al.. (2014). Automated Detection of Activity Transitions for Prompting. IEEE Transactions on Human-Machine Systems. 45(5). 575–585. 46 indexed citations

10.

Feuz, Kyle & Diane J. Cook. (2014). Heterogeneous transfer learning for activity recognition using heuristic search techniques. International Journal of Pervasive Computing and Communications. 10(4). 393–418. 22 indexed citations

11.

Feuz, Kyle, et al.. (2014). C-66 * Prompting Technologies: Is Prompting during Activity Transition More Effective than Time-Based Prompting?. Archives of Clinical Neuropsychology. 29(6). 598–598. 4 indexed citations

12.

Feuz, Kyle & Diane J. Cook. (2013). Real-Time Annotation Tool (RAT). National Conference on Artificial Intelligence. 6 indexed citations

13.

Cook, Diane J., Kyle Feuz, & Narayanan C. Krishnan. (2013). Transfer learning for activity recognition: a survey. Knowledge and Information Systems. 36(3). 537–556. 335 indexed citations breakdown →

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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