Sakti Pramanik
- Molecular Biology
- Computer Vision and Pattern Recognition top 2%
- Computer Networks and Communications top 2%
- Signal Processing top 2%
- Ecology top 5%
- Topics
- Data Management and Algorithms (37 papers)Algorithms and Data Compression (36 papers)Advanced Database Systems and Queries (21 papers)
- Cited by
- Signal ProcessingComputer Vision and Pattern RecognitionComputer Networks and Communications
- Partner nations
- United StatesSouth KoreaIndia
In The Last Decade
Sakti Pramanik
80 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Molecular Biology 648
- Computer Vision and Pattern Recognition 520
- Computer Networks and Communications 436
- Signal Processing 434
- Ecology 427
Countries citing papers authored by Sakti Pramanik
This map shows the geographic impact of Sakti Pramanik'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 Sakti Pramanik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sakti Pramanik more than expected).
Fields of papers citing papers by Sakti Pramanik
This network shows the impact of papers produced by Sakti Pramanik. 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 Sakti Pramanik. The network helps show where Sakti Pramanik may publish in the future.
Co-authorship network of co-authors of Sakti Pramanik
This figure shows the co-authorship network connecting the top 25 collaborators of Sakti Pramanik. A scholar is included among the top collaborators of Sakti Pramanik 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 Sakti Pramanik. Sakti Pramanik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | Clustering Non-Ordered Discrete Data * | 4 |
| 3 | 9 | |
| 4 | A Histogramm with Perceptually Smooth Color Transition for Image Retrieval. | 13 |
| 5 | 4 | |
| 6 | A new version of the RDP (Ribosomal Database Project)breakdown → | 840 |
| 7 | 7 | |
| 8 | 12 | |
| 9 | 2 | |
| 10 | 13 | |
| 11 | 87 | |
| 12 | An efficient method for multiple sequence alignment. | 1 |
| 13 | 2 | |
| 14 | 54 | |
| 15 | Distributed linear hashing and parallel projection in main memory databases | 16 |
| 16 | Distributed Linear Hashing for Main Memory Databases. | 2 |
| 17 | On the Data Distribution Problems for Range Queries. | 2 |
| 18 | 2 | |
| 19 | HCB-tree : A B-tree Structure for Parallel Processing | 3 |
| 20 | Hardware organization for nonnumeric processing | 1 |
About Sakti Pramanik
Sakti Pramanik is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence, having authored 84 papers that have together received 2.3k indexed citations. Recurring topics across this work include Data Management and Algorithms (37 papers), Algorithms and Data Compression (36 papers) and Advanced Database Systems and Queries (21 papers). The work is most often cited by research in Signal Processing (434 citations), Computer Vision and Pattern Recognition (520 citations) and Computer Networks and Communications (436 citations). Sakti Pramanik has collaborated with scholars based in United States, South Korea and India. Frequent co-authors include Gang Qian, Shamik Sural, Sungwon Jung, Myoung Ho Kim, James R. Cole, B. Maidak, J.M. Tiedje, Bo Li, Thomas M. Schmidt and Timothy Lilburn. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and PLANT PHYSIOLOGY.
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.