N. Krishnamoorthy
Impact in
- Analytical Chemistry top 5%
- Spectroscopy and Chemometric Analyses
- Plant Science top 10%
- Smart Agriculture and AI
- Leaf Properties and Growth Measurement
- Plant Disease Management Techniques
- Date Palm Research Studies
Papers in
-
- Artificial Intelligence in Healthcare 2
-
- Cloud Computing and Resource Management 3
- Technology and Data Analysis 2
- Co-authors
- C. S. Pavan KumarL V Narasimha PrasadHaftom Baraki AbrahaV E SathishkumarK. Nirmala DeviP JambulingamN. KarthikeyanN. Shanthi
- Journals
- IEEE Access (1 paper)Environmental Research (1 paper)Neural Computing and Applications (1 paper)Scalable Computing Practice and Experience (2 papers)Information Technology And Control (1 paper)
- Partner nations
- IndiaSouth KoreaChina
In The Last Decade
N. Krishnamoorthy
26 papers receiving 281 citations
Hit Papers
Peers
Comparison fields: 5 of 66
- Analytical Chemistry 92
- Plant Science 189
- Health Information Management 20
- Information Systems 26
- Artificial Intelligence 30
Countries citing papers authored by N. Krishnamoorthy
This map shows the geographic impact of N. Krishnamoorthy'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. Krishnamoorthy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Krishnamoorthy more than expected).
Fields of papers citing papers by N. Krishnamoorthy
This network shows the impact of papers produced by N. Krishnamoorthy. 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. Krishnamoorthy. The network helps show where N. Krishnamoorthy may publish in the future.
Co-authors
The 20 scholars most cited alongside N. Krishnamoorthy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 3 | |
| 6 | 2024 | 9 | |
| 7 | 2023 | 3 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 0 | |
| 11 | 2023 | 1 | |
| 12 | 2023 | 3 | |
| 13 | 2022 | 2 | |
| 14 | Rice leaf diseases prediction using deep neural networks with transfer learning Hit paper breakdown → | 2021 | 200 |
| 15 | 2021 | 9 | |
| 16 | 2018 | 5 | |
| 17 | 2017 | 1 | |
| 18 | 2016 | 9 | |
| 19 | 2015 | 6 | |
| 20 | Absolute frequency measurements of the $D_1$ lines in $^{39}K, ^{85}Rb,$ and $^{87}Rb$ with $\\sim$ 0.1 ppb uncertainty | 2004 | 0 |
About N. Krishnamoorthy
N. Krishnamoorthy is a scholar working on Health Information Management, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence, having authored 33 papers that have together received 306 indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (3 papers), Cloud Computing and Resource Management (3 papers), Smart Agriculture and AI (3 papers), COVID-19 diagnosis using AI (3 papers), Retinal Imaging and Analysis (2 papers), Artificial Intelligence in Healthcare (2 papers), Lung Cancer Diagnosis and Treatment (2 papers) and Technology and Data Analysis (2 papers). The work is most often cited by research in Analytical Chemistry (92 citations), Plant Science (189 citations), Health Information Management (20 citations), Information Systems (26 citations) and Artificial Intelligence (30 citations). N. Krishnamoorthy has collaborated with scholars based in India, South Korea and China. Frequent co-authors include C. S. Pavan Kumar, L V Narasimha Prasad, Haftom Baraki Abraha, V E Sathishkumar, K. Nirmala Devi, P Jambulingam, N. Karthikeyan, N. Shanthi, T R Mahesh and N. Saravanan. Their work appears in journals such as IEEE Access, Environmental Research, Neural Computing and Applications, Scalable Computing Practice and Experience and Information Technology And Control.
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.