Josh Harguess
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Signal Processing top 10%
- Aerospace Engineering
- Media Technology top 10%
- Co-authors
- J.K. AggarwalChangbo HuShibin ParameswaranShalini GuptaPedro A. ForeroMikel RodríguezKeith SullivanJohn M. Irvine
- Topics
- Anomaly Detection Techniques and Applications (11 papers)Adversarial Robustness in Machine Learning (10 papers)Advanced Vision and Imaging (9 papers)
- Journals
- IEEE Transactions on Signal ProcessingProceedings - International Conference on Pattern Recognition2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
- Partner nations
- United States
In The Last Decade
Josh Harguess
39 papers receiving 281 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 198
- Artificial Intelligence 90
- Signal Processing 54
- Aerospace Engineering 43
- Media Technology 37
Countries citing papers authored by Josh Harguess
This map shows the geographic impact of Josh Harguess'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 Josh Harguess with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josh Harguess more than expected).
Fields of papers citing papers by Josh Harguess
This network shows the impact of papers produced by Josh Harguess. 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 Josh Harguess. The network helps show where Josh Harguess may publish in the future.
Co-authorship network of co-authors of Josh Harguess
This figure shows the co-authorship network connecting the top 25 collaborators of Josh Harguess. A scholar is included among the top collaborators of Josh Harguess 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 Josh Harguess. Josh Harguess is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 8 | |
| 6 | 2 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 30 | |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 1 | |
| 14 | 4 | |
| 15 | 25 | |
| 16 | 23 | |
| 17 | 6 | |
| 18 | 7 | |
| 19 | 6 | |
| 20 | 16 |
About Josh Harguess
Josh Harguess is a scholar working on Computer Vision and Pattern Recognition, Health Informatics and Media Technology, having authored 44 papers that have together received 308 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (11 papers), Adversarial Robustness in Machine Learning (10 papers) and Advanced Vision and Imaging (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (198 citations), Signal Processing (54 citations) and Media Technology (37 citations). Josh Harguess has collaborated with scholars based in United States. Frequent co-authors include J.K. Aggarwal, Changbo Hu, Shibin Parameswaran, Shalini Gupta, Pedro A. Forero, Mikel Rodríguez, Keith Sullivan, John M. Irvine and Yongjun Tan. Their work appears in journals such as IEEE Transactions on Signal Processing, Proceedings - International Conference on Pattern Recognition and 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
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.