Daniel H. Wilson

540 total citations
10 papers, 121 citations indexed

About

Daniel H. Wilson is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Daniel H. Wilson has authored 10 papers receiving a total of 121 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Daniel H. Wilson's work include Context-Aware Activity Recognition Systems (3 papers), Time Series Analysis and Forecasting (2 papers) and Robotics and Sensor-Based Localization (2 papers). Daniel H. Wilson is often cited by papers focused on Context-Aware Activity Recognition Systems (3 papers), Time Series Analysis and Forecasting (2 papers) and Robotics and Sensor-Based Localization (2 papers). Daniel H. Wilson collaborates with scholars based in United States, Mexico and Jordan. Daniel H. Wilson's co-authors include Chris Atkeson, Anna C. J. Long, Margaret H. Szymanski, James D. Thornton, Paul M. Aoki, Safwan Wshah, Xiaohan Zhang, Allison Woodruff, Matthai Philipose and Waqas Sultani and has published in prestigious journals such as International Journal of Computer Vision, Remote Sensing and Figshare.

In The Last Decade

Daniel H. Wilson

9 papers receiving 111 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel H. Wilson United States	6	71	25	24	23	16	10	121
Ron Frederick United States	3	56 0.8×	38 1.5×	8 0.3×	38 1.7×	6 0.4×	4	110
Zhourong Chen Hong Kong	7	82 1.2×	9 0.4×	87 3.6×	19 0.8×	3 0.2×	9	164
Brandon Barbello United States	2	87 1.2×	29 1.2×	33 1.4×	41 1.8×	4 0.3×	2	269
Martial Michel United States	7	134 1.9×	17 0.7×	83 3.5×	15 0.7×	5 0.3×	19	223
O. Beltramello Switzerland	5	45 0.6×	22 0.9×	6 0.3×	24 1.0×	8 0.5×	7	121
Nilesh Chakraborty India	8	22 0.3×	28 1.1×	45 1.9×	11 0.5×	11 0.7×	26	177
Luc Julia United States	7	67 0.9×	36 1.4×	92 3.8×	36 1.6×	20 1.3×	15	168
Jiajun Wu China	5	33 0.5×	10 0.4×	70 2.9×	7 0.3×	7 0.4×	14	135
Michiel de Jong United States	7	29 0.4×	20 0.8×	116 4.8×	8 0.3×	3 0.2×	11	215
Feng-Tso Sun United States	4	120 1.7×	44 1.8×	63 2.6×	11 0.5×	2 0.1×	8	168

Countries citing papers authored by Daniel H. Wilson

Since Specialization

Citations

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

Fields of papers citing papers by Daniel H. Wilson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel H. Wilson. 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 Daniel H. Wilson. The network helps show where Daniel H. Wilson may publish in the future.

Co-authorship network of co-authors of Daniel H. Wilson

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

All Works

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10 of 10 papers shown

1.

Beelen, Kaspar, et al.. (2025). Whose news? Critical methods for assessing bias in large historical datasets. 1.

2.

Wilson, Daniel H., Xiaohan Zhang, Waqas Sultani, & Safwan Wshah. (2023). Image and Object Geo-Localization. International Journal of Computer Vision. 132(4). 1350–1392. 12 indexed citations

3.

Wilson, Daniel H., et al.. (2022). Object Tracking and Geo-Localization from Street Images. Remote Sensing. 14(11). 2575–2575. 9 indexed citations

4.

Allin, Sonya, Ashok J. Bharucha, John Zimmerman, et al.. (2018). Toward the Automatic Assessment of Behavioral Distrubances of Dementia. Figshare. 3 indexed citations

5.

Wilson, Daniel H.. (2015). Chasing Our Science Fiction Future. 245–245. 4 indexed citations

6.

Wilson, Daniel H.. (2007). How to Build a Robot Army: Tips on Defending Planet Earth Against Alien Invaders, Ninjas, and Zombies. 2 indexed citations

7.

Wilson, Daniel H. & Matthai Philipose. (2005). Maximum a posteriori path estimation with input trace perturbation: algorithms and application to credible rating of human routines. International Joint Conference on Artificial Intelligence. 895–901. 7 indexed citations

8.

Atkeson, Chris & Daniel H. Wilson. (2005). Assistive intelligent environments for automatic health monitoring. 32 indexed citations

9.

Wilson, Daniel H., Anna C. J. Long, & Chris Atkeson. (2005). A context-aware recognition survey for data collection using ubiquitous sensors in the home. 1865–1868. 23 indexed citations

10.

Aoki, Paul M., et al.. (2003). The Mad Hatter´s Cocktail Party: A Social Mobile Audio Space Supporting Multiple Simultaneous Conversations. arXiv (Cornell University). 29 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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