Arun K. Pujari
- Artificial Intelligence top 2%
- Information Systems top 1%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Signal Processing top 2%
- Co-authors
- Vineet PadmanabhanVikas KumarSanjay RawatKuldip K. PaliwalAlok SharmaMalay Kishore DuttaB. L. DeekshatuluC. S. Sastry
- Topics
- Data Management and Algorithms (14 papers)Image Retrieval and Classification Techniques (13 papers)Recommender Systems and Techniques (11 papers)
In The Last Decade
Arun K. Pujari
79 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Artificial Intelligence 706
- Information Systems 592
- Computer Networks and Communications 358
- Computer Vision and Pattern Recognition 356
- Signal Processing 323
Countries citing papers authored by Arun K. Pujari
This map shows the geographic impact of Arun K. Pujari'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 Arun K. Pujari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arun K. Pujari more than expected).
Fields of papers citing papers by Arun K. Pujari
This network shows the impact of papers produced by Arun K. Pujari. 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 Arun K. Pujari. The network helps show where Arun K. Pujari may publish in the future.
Co-authorship network of co-authors of Arun K. Pujari
This figure shows the co-authorship network connecting the top 25 collaborators of Arun K. Pujari. A scholar is included among the top collaborators of Arun K. Pujari 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 Arun K. Pujari. Arun K. Pujari 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 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 42 | |
| 6 | 1 | |
| 7 | Opportunistic Consensus Clustering. | 1 |
| 8 | A tighter error bound for decision tree learning using PAC learnability | 3 |
| 9 | 3 | |
| 10 | Intrusion Detection Using Text Processing Techniques with a Binary-Weighted Cosine Metric | 28 |
| 11 | 2 | |
| 12 | Bitplane Based Area Morphology for CBIR. | 1 |
| 13 | 32 | |
| 14 | An Adaptive Character Recognizer for Telugu Scripts Using Multiresolution Analysis, Associative Memory. | 12 |
| 15 | 3 | |
| 16 | A New Framework for Reasoning about Points, Intervals and Durations | 19 |
| 17 | 1 | |
| 18 | OFF-LINE SHORTHAND RECOGNITION SYSTEM | 2 |
| 19 | 1 | |
| 20 | 1 |
About Arun K. Pujari
Arun K. Pujari is a scholar working on Computer Graphics and Computer-Aided Design, Signal Processing and Computer Vision and Pattern Recognition, having authored 83 papers that have together received 1.6k indexed citations. Recurring topics across this work include Data Management and Algorithms (14 papers), Image Retrieval and Classification Techniques (13 papers) and Recommender Systems and Techniques (11 papers). The work is most often cited by research in Signal Processing (323 citations), Information Systems (592 citations) and Artificial Intelligence (706 citations). Arun K. Pujari has collaborated with scholars based in India, Australia and Taiwan. Frequent co-authors include Vineet Padmanabhan, Vikas Kumar, Sanjay Rawat, Kuldip K. Paliwal, Alok Sharma, Malay Kishore Dutta, B. L. Deekshatulu, C. S. Sastry, M. Sreenivasa Rao and Abdul Sattar. Their work appears in journals such as Expert Systems with Applications, Pattern Recognition and Information 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.