Sherry E. Hammel
- Aerospace Engineering top 5%
- Inertial Sensor and Navigation 2
- Artificial Intelligence top 5%
- Target Tracking and Data Fusion in Sensor Networks 7
- Neural Networks and Applications 1
- Ocean Engineering top 5%
- Oceanography top 10%
- Control and Systems Engineering top 10%
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- Indoor and Outdoor Localization Technologies 3
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- Structural Health Monitoring Techniques 2
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- Statistical Methods and Bayesian Inference 1
- Statistical Distribution Estimation and Applications 1
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- Image and Signal Denoising Methods 1
- Journals
- Computers & Mathematics with Applications (1 paper)IEEE Transactions on Aerospace and Electronic Systems (1 paper)IEEE Transactions on Automatic Control (1 paper)
- Partner nations
- United States
In The Last Decade
Sherry E. Hammel
9 papers receiving 526 citations
Peers
Comparison fields: 5 of 37
- Aerospace Engineering 350
- Artificial Intelligence 443
- Ocean Engineering 97
- Oceanography 63
- Control and Systems Engineering 96
Countries citing papers authored by Sherry E. Hammel
This map shows the geographic impact of Sherry E. Hammel'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 Sherry E. Hammel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sherry E. Hammel more than expected).
Fields of papers citing papers by Sherry E. Hammel
This network shows the impact of papers produced by Sherry E. Hammel. 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 Sherry E. Hammel. The network helps show where Sherry E. Hammel may publish in the future.
Co-authorship network
The 4 scholars most cited alongside Sherry E. Hammel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 0 | |
| 2 | 2002 | 0 | |
| 3 | 2002 | 1 | |
| 4 | 1996 | 1 | |
| 5 | 1995 | 1 | |
| 6 | 1994 | 0 | |
| 7 | 1994 | 1 | |
| 8 | 1993 | 1 | |
| 9 | 1989 | 76 | |
| 10 | 1985 | 125 | |
| 11 | 1983 | 373 | |
| 12 | 1983 | 10 |
About Sherry E. Hammel
Sherry E. Hammel is a scholar working on Artificial Intelligence, Statistics and Probability and Aerospace Engineering, having authored 12 papers that have together received 589 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (7 papers), Indoor and Outdoor Localization Technologies (3 papers), Structural Health Monitoring Techniques (2 papers), Inertial Sensor and Navigation (2 papers), Statistical Methods and Bayesian Inference (1 paper), Image and Signal Denoising Methods (1 paper), Neural Networks and Applications (1 paper) and Statistical Distribution Estimation and Applications (1 paper). The work is most often cited by research in Aerospace Engineering (350 citations), Artificial Intelligence (443 citations) and Ocean Engineering (97 citations). Sherry E. Hammel has collaborated with scholars based in United States. Frequent co-authors include Vincent Aidala, Kai Gong, A.G. Lindgren and Frank O’Brien. Their work appears in journals such as Computers & Mathematics with Applications, IEEE Transactions on Aerospace and Electronic Systems, IEEE Transactions on Automatic Control, Perceptual and Motor Skills and IEEE International Conference on Acoustics Speech and Signal Processing.
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.