N. Keshava

4.0k total citations · 2 hit papers
12 papers, 3.2k citations indexed

About

N. Keshava is a scholar working on Media Technology, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, N. Keshava has authored 12 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Media Technology, 4 papers in Aerospace Engineering and 3 papers in Artificial Intelligence. Recurrent topics in N. Keshava's work include Remote-Sensing Image Classification (8 papers), Geochemistry and Geologic Mapping (3 papers) and Spectroscopy and Chemometric Analyses (3 papers). N. Keshava is often cited by papers focused on Remote-Sensing Image Classification (8 papers), Geochemistry and Geologic Mapping (3 papers) and Spectroscopy and Chemometric Analyses (3 papers). N. Keshava collaborates with scholars based in United States. N. Keshava's co-authors include John F. Mustard, Channa Keshava, Wen‐Zong Whong, Gu Zhou, José M. F. Moura, José J. G. Moura, Alexander Lin, Carolyn E. Mountford, Saadallah Ramadan and John P. Kerekes and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Signal Processing and IEEE Signal Processing Magazine.

In The Last Decade

N. Keshava

11 papers receiving 3.1k citations

Hit Papers

Spectral unmixing 2002 2026 2010 2018 2002 2002 500 1000 1.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
N. Keshava United States 6 2.5k 1.3k 636 454 454 12 3.2k
M. Parente United States 24 2.5k 1.0× 1.6k 1.2× 594 0.9× 625 1.4× 333 0.7× 115 4.5k
J. Chanussot France 16 2.8k 1.1× 1.8k 1.4× 548 0.9× 359 0.8× 270 0.6× 30 3.2k
Mathieu Fauvel France 16 4.2k 1.7× 2.9k 2.2× 910 1.4× 485 1.1× 513 1.1× 24 4.8k
Behnood Rasti Germany 25 2.5k 1.0× 973 0.7× 409 0.6× 423 0.9× 167 0.4× 72 3.2k
Thomas G. Chrien United States 11 1.3k 0.5× 737 0.5× 700 1.1× 505 1.1× 205 0.5× 45 2.7k
Javier Calpe‐Maravilla Spain 14 1.2k 0.5× 867 0.6× 401 0.6× 222 0.5× 191 0.4× 34 1.8k
Maurice Craig Australia 9 1.7k 0.7× 630 0.5× 633 1.0× 898 2.0× 407 0.9× 21 2.7k
Marian-Daniel Iordache Belgium 19 2.1k 0.8× 1.2k 0.9× 416 0.7× 155 0.3× 154 0.3× 37 2.6k
Jason Brazile Switzerland 9 1.2k 0.5× 792 0.6× 709 1.1× 173 0.4× 221 0.5× 24 2.0k
Giovanna Trianni Italy 10 1.4k 0.6× 946 0.7× 423 0.7× 170 0.4× 171 0.4× 24 1.9k

Countries citing papers authored by N. Keshava

Since Specialization
Citations

This map shows the geographic impact of N. Keshava'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 N. Keshava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Keshava more than expected).

Fields of papers citing papers by N. Keshava

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N. Keshava. 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 N. Keshava. The network helps show where N. Keshava may publish in the future.

Co-authorship network of co-authors of N. Keshava

This figure shows the co-authorship network connecting the top 25 collaborators of N. Keshava. A scholar is included among the top collaborators of N. Keshava 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 N. Keshava. N. Keshava is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Keshava, N., et al.. (2019). A Survey of Popular Image and Text analysis Techniques. 1–8. 8 indexed citations
2.
Lin, Alexander, et al.. (2011). Algorithms for characterizing brain metabolites in two-dimensional in vivo MR correlation spectroscopy. PubMed. 19. 4929–4934. 3 indexed citations
3.
Keshava, N.. (2004). Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries. IEEE Transactions on Geoscience and Remote Sensing. 42(7). 1552–1565. 270 indexed citations
4.
Kerekes, John P., et al.. (2003). Linear unmixing performance forecasting. 3. 1676–1678. 3 indexed citations
5.
Keshava, N. & John F. Mustard. (2002). Spectral unmixing. IEEE Signal Processing Magazine. 1130 indexed citations breakdown →
6.
Keshava, N.. (2002). Best bands selection for detection in hyperspectral processing. 5. 3149–3152. 26 indexed citations
7.
Keshava, N. & José J. G. Moura. (2002). Terrain classification in polarimetric SAR using wavelet packets. 1. 555–558. 1 indexed citations
8.
Keshava, N. & José M. F. Moura. (2002). Robust classification of targets in POL-SAR using wavelet packets. 105–110.
9.
Keshava, N. & John F. Mustard. (2002). Spectral unmixing. IEEE Signal Processing Magazine. 19(1). 44–57. 1721 indexed citations breakdown →
10.
Keshava, N. & José M. F. Moura. (2002). Wavelets and random processes: optimal matching in the Bhattacharyya sense. 993–997. 2 indexed citations
11.
Keshava, Channa, et al.. (1999). Genomic instability in silica- and cadmium chloride-transformed BALB/c-3T3 and tumor cell lines by random amplified polymorphic DNA analysis. Mutation research. Fundamental and molecular mechanisms of mutagenesis. 425(1). 117–123. 13 indexed citations
12.
Keshava, N. & José M. F. Moura. (1999). Matching wavelet packets to Gaussian random processes. IEEE Transactions on Signal Processing. 47(6). 1604–1614. 2 indexed citations

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.

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