D.M. Wilkes
- Artificial Intelligence top 5%
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 5%
- Social Psychology top 10%
- Co-authors
- J.A. CadzowRichard ShiaviStephen E. SilvermanMarilyn K. SilvermanA. OzdasGang LiangXiaochun WangK. Kawamura
- Topics
- Blind Source Separation Techniques (13 papers)Control Systems and Identification (10 papers)Direction-of-Arrival Estimation Techniques (8 papers)
- Partner nations
- United StatesChinaTürkiye
In The Last Decade
D.M. Wilkes
89 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 331
- Signal Processing 213
- Computer Vision and Pattern Recognition 205
- Control and Systems Engineering 170
- Social Psychology 143
Countries citing papers authored by D.M. Wilkes
This map shows the geographic impact of D.M. Wilkes'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 D.M. Wilkes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D.M. Wilkes more than expected).
Fields of papers citing papers by D.M. Wilkes
This network shows the impact of papers produced by D.M. Wilkes. 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 D.M. Wilkes. The network helps show where D.M. Wilkes may publish in the future.
Co-authorship network of co-authors of D.M. Wilkes
This figure shows the co-authorship network connecting the top 25 collaborators of D.M. Wilkes. A scholar is included among the top collaborators of D.M. Wilkes 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 D.M. Wilkes. D.M. Wilkes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 3 | |
| 3 | 28 | |
| 4 | 3 | |
| 5 | 9 | |
| 6 | A Fast Distance-Based Outlier Detection Technique. | 2 |
| 7 | 15 | |
| 8 | Predicting severity of mental state using vocal output characteristics. | 1 |
| 9 | Distinguishing high risk suicidal subjects among depressed subjects using mel-frequency cepstrum coefficients and cross validation technique. | 2 |
| 10 | A computational neuroscience model of working memory with application to robot perceptual learning | 6 |
| 11 | 1 | |
| 12 | 150 | |
| 13 | 35 | |
| 14 | ISAC Humanoid: An Architecture for Learning and Emotion | 4 |
| 15 | 39 | |
| 16 | Toward perception-based navigation using EgoSphere. | 4 |
| 17 | 1 | |
| 18 | 4 | |
| 19 | 0 | |
| 20 | 1 |
About D.M. Wilkes
D.M. Wilkes is a scholar working on Signal Processing, Control and Systems Engineering and Computer Vision and Pattern Recognition, having authored 94 papers that have together received 1.1k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (13 papers), Control Systems and Identification (10 papers) and Direction-of-Arrival Estimation Techniques (8 papers). The work is most often cited by research in Signal Processing (213 citations), Aging (21 citations) and Experimental and Cognitive Psychology (141 citations). D.M. Wilkes has collaborated with scholars based in United States, China and Türkiye. Frequent co-authors include J.A. Cadzow, Richard Shiavi, Stephen E. Silverman, Marilyn K. Silverman, A. Ozdas, Gang Liang, Xiaochun Wang, K. Kawamura, Adnan Al‐Smadi and Paul Fleming. Their work appears in journals such as Journal of Neuroscience, Scientific Reports and IEEE Transactions on Image 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.