David W. Opitz
Impact in
- Artificial Intelligence top 0.5%
- Neural Networks and Applications
- Machine Learning and Data Classification
- Imbalanced Data Classification Techniques
- Evolutionary Algorithms and Applications
- Anomaly Detection Techniques and Applications
- Metaheuristic Optimization Algorithms Research
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- Face and Expression Recognition
Papers in
-
- Neural Networks and Applications 12
- Machine Learning and Data Classification 7
- Evolutionary Algorithms and Applications 4
- Imbalanced Data Classification Techniques 2
- Metaheuristic Optimization Algorithms Research 2
- Co-authors
- Richard Maclin (3 shared papers)Jude Shavlik (5 shared papers)Joanne Winne (1 shared paper)C. Kenneth Brewer (1 shared paper)Roland L. Redmond (1 shared paper)Subhash C. Basak (4 shared papers)Brian D. Gute (4 shared papers)K. Balasubramanian (3 shared papers)
- Journals
- Journal of Artificial Intelligence Research (2 papers)Connection Science (1 paper)Photogrammetric Engineering & Remote Sensing (1 paper)Genetic and Evolutionary Computation Conference (2 papers)Journal of Chemical Information and Computer Sciences (1 paper)
- Partner nations
- United StatesGermany
In The Last Decade
David W. Opitz
23 papers receiving 2.9k citations
David W. Opitz's Hit Papers
Peers
Comparison fields: 5 of 187
- Artificial Intelligence 1.6k
- Computer Vision and Pattern Recognition 589
- Signal Processing 212
- Health Information Management 74
- Computational Theory and Mathematics 213
Countries citing papers authored by David W. Opitz
This map shows the geographic impact of David W. Opitz'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 David W. Opitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David W. Opitz more than expected).
Fields of papers citing papers by David W. Opitz
This network shows the impact of papers produced by David W. Opitz. 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 David W. Opitz. The network helps show where David W. Opitz may publish in the future.
Co-authors
The 10 scholars most cited alongside David W. Opitz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Popular Ensemble Methods: An Empirical Study Hit paper breakdown → | 1999 | 1973 |
| 2 | 1996 | 214 | |
| 3 | Feature selection for ensembles | 1999 | 200 |
| 4 | Generating Accurate and Diverse Members of a Neural-Network Ensemble | 1995 | 190 |
| 5 | An empirical evaluation of bagging and boosting | 1997 | 176 |
| 6 | 2005 | 155 | |
| 7 | 2000 | 66 | |
| 8 | 2002 | 35 | |
| 9 | 1997 | 34 | |
| 10 | Heuristically Expanding Knowledge-Based Neural Networks. | 1993 | 13 |
| 11 | A Genetic Algorithm Approach for Creating Neural-Network Ensembles | 1999 | 8 |
| 12 | Hazard assessment modeling: an evolutionary ensemble approach | 1999 | 7 |
| 13 | An anytime approach to connectionist theory refinement: refining the topologies of knowledge-based neural networks | 1996 | 6 |
| 14 | Optimal grasp points: computational theory and human psychophysics | 1993 | 5 |
| 15 | GROUND SURFACE EXTRACTION FROM SIDE-SCAN (VEHICULAR) LIDAR | 2006 | 5 |
| 16 | A comparison of grasping real and virtual objects | 1996 | 5 |
| 17 | AN APPROACH FOR COLLECTION OF GEOSPECIFIC 3D FEATURES FROM TERRESTRIAL LIDAR | 2008 | 3 |
| 18 | Use of Statistical and Neural Net Methods in Predicting Toxicity of Chemicals: A Hierarchical QSAR Approach | 1999 | 2 |
| 19 | Feature Extraction from Digital Imagery: A Hierarchical Method. | 2001 | 2 |
| 20 | 2002 | 2 |
About David W. Opitz
David W. Opitz is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Control and Systems Engineering and Environmental Engineering, having authored 23 papers that have together received 3.1k indexed citations. Recurring topics across this work include Neural Networks and Applications (12 papers), Machine Learning and Data Classification (7 papers), Evolutionary Algorithms and Applications (4 papers), Computational Drug Discovery Methods (3 papers), Imbalanced Data Classification Techniques (2 papers), 3D Surveying and Cultural Heritage (2 papers), Remote Sensing and LiDAR Applications (2 papers) and Metaheuristic Optimization Algorithms Research (2 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Computer Vision and Pattern Recognition (589 citations), Signal Processing (212 citations), Health Information Management (74 citations) and Computational Theory and Mathematics (213 citations). David W. Opitz has collaborated with scholars based in United States and Germany. Frequent co-authors include Richard Maclin, Jude Shavlik, Joanne Winne, C. Kenneth Brewer, Roland L. Redmond, Subhash C. Basak, Brian D. Gute, K. Balasubramanian, Gregory D. Grunwald and HH Bülthoff. Their work appears in journals such as Journal of Artificial Intelligence Research, Connection Science, Photogrammetric Engineering & Remote Sensing, Genetic and Evolutionary Computation Conference and Journal of Chemical Information and Computer Sciences.
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.