Ardhendu Behera
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Environmental Engineering top 10%
- Signal Processing top 5%
- Co-authors
- Ella PereiraPradeep HewageMarcello TrovatiYonghuai LiuMorteza GhahremaniFrancesco PalmieriBappaditya DebnathMary O’Brien
- Topics
- Human Pose and Action Recognition (10 papers)Video Surveillance and Tracking Methods (7 papers)Context-Aware Activity Recognition Systems (5 papers)
- Partner nations
- United KingdomSwitzerlandChina
In The Last Decade
Ardhendu Behera
36 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Computer Vision and Pattern Recognition 338
- Artificial Intelligence 229
- Electrical and Electronic Engineering 181
- Environmental Engineering 137
- Signal Processing 105
Countries citing papers authored by Ardhendu Behera
This map shows the geographic impact of Ardhendu Behera'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 Ardhendu Behera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ardhendu Behera more than expected).
Fields of papers citing papers by Ardhendu Behera
This network shows the impact of papers produced by Ardhendu Behera. 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 Ardhendu Behera. The network helps show where Ardhendu Behera may publish in the future.
Co-authorship network of co-authors of Ardhendu Behera
This figure shows the co-authorship network connecting the top 25 collaborators of Ardhendu Behera. A scholar is included among the top collaborators of Ardhendu Behera 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 Ardhendu Behera. Ardhendu Behera is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 7 | |
| 3 | 24 | |
| 4 | 1 | |
| 5 | 56 | |
| 6 | 24 | |
| 7 | 23 | |
| 8 | 76 | |
| 9 | 4 | |
| 10 | 147 | |
| 11 | 50 | |
| 12 | Temporal convolutional neural (TCN) network for an effective weather forecasting using time-series data from the local weather stationbreakdown → | 370 |
| 13 | 7 | |
| 14 | 21 | |
| 15 | 33 | |
| 16 | 19 | |
| 17 | 30 | |
| 18 | 16 | |
| 19 | 1 | |
| 20 | A research agenda for assessing the utility of document annotations in multimedia databases of meeting recordings. | 8 |
About Ardhendu Behera
Ardhendu Behera is a scholar working on Computer Vision and Pattern Recognition, Human-Computer Interaction and Automotive Engineering, having authored 36 papers that have together received 1.1k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (10 papers), Video Surveillance and Tracking Methods (7 papers) and Context-Aware Activity Recognition Systems (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (338 citations), Human-Computer Interaction (67 citations) and Signal Processing (105 citations). Ardhendu Behera has collaborated with scholars based in United Kingdom, Switzerland and China. Frequent co-authors include Ella Pereira, Pradeep Hewage, Marcello Trovati, Yonghuai Liu, Morteza Ghahremani, Francesco Palmieri, Bappaditya Debnath, Mary O’Brien, Motonori Yamaguchi and Nik Bessis. Their work appears in journals such as PLoS ONE, IEEE Transactions on Image Processing and Experimental Brain Research.
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.