Prabhjot Kaur

1.0k total citations · 1 hit paper
57 papers, 672 citations indexed

About

Prabhjot Kaur is a scholar working on Computer Networks and Communications, Plant Science and Electrical and Electronic Engineering. According to data from OpenAlex, Prabhjot Kaur has authored 57 papers receiving a total of 672 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Networks and Communications, 13 papers in Plant Science and 11 papers in Electrical and Electronic Engineering. Recurrent topics in Prabhjot Kaur's work include Smart Agriculture and AI (11 papers), Leaf Properties and Growth Measurement (8 papers) and Wireless Communication Networks Research (7 papers). Prabhjot Kaur is often cited by papers focused on Smart Agriculture and AI (11 papers), Leaf Properties and Growth Measurement (8 papers) and Wireless Communication Networks Research (7 papers). Prabhjot Kaur collaborates with scholars based in India, United States and Saudi Arabia. Prabhjot Kaur's co-authors include Shilpi Harnal, Vinay Gautam, Santar Pal Singh, Mukund Pratap Singh, Rajeev Tiwari, Arwa Mashat, Shuchi Upadhyay, Surbhi Bhatia, Arun Khosla and Rakesh K. Sindhu and has published in prestigious journals such as Sensors, International Journal of Environmental Research and Public Health and International Journal of Biological Macromolecules.

In The Last Decade

Prabhjot Kaur

47 papers receiving 608 citations

Hit Papers

Recognition of Leaf Disea... 2022 2026 2023 2024 2022 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Prabhjot Kaur India 13 319 143 127 87 53 57 672
Naresh Kumar Trivedi India 13 319 1.0× 49 0.3× 119 0.9× 24 0.3× 30 0.6× 73 615
Vinay Gautam India 14 595 1.9× 53 0.4× 211 1.7× 27 0.3× 89 1.7× 90 881
Abhineet Anand India 11 208 0.7× 77 0.5× 67 0.5× 32 0.4× 20 0.4× 49 490
Nikos Petrellis Greece 9 151 0.5× 57 0.4× 59 0.5× 54 0.6× 24 0.5× 62 358
Poonam Dhiman India 8 249 0.8× 62 0.4× 120 0.9× 25 0.3× 18 0.3× 14 498
Geeta Rani India 14 265 0.8× 52 0.4× 88 0.7× 45 0.5× 37 0.7× 58 643
G. Sambasivam India 9 189 0.6× 68 0.5× 75 0.6× 21 0.2× 25 0.5× 20 447
Vishnu Kumar Kaliappan India 10 201 0.6× 60 0.4× 98 0.8× 46 0.5× 32 0.6× 51 449
Vaibhav Tiwari India 9 195 0.6× 45 0.3× 76 0.6× 30 0.3× 24 0.5× 26 347
Jiang Lu China 12 269 0.8× 42 0.3× 126 1.0× 23 0.3× 51 1.0× 39 684

Countries citing papers authored by Prabhjot Kaur

Since Specialization
Citations

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

Fields of papers citing papers by Prabhjot Kaur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Prabhjot Kaur

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

All Works

20 of 20 papers shown
1.
Huang, Guohong, Gregory J. Tsongalis, Laura J. Tafe, et al.. (2025). Diagnostic next-generation sequencing to detect MYD88 L265P in Lymphoplasmacytic lymphoma compared to ddPCR. Experimental and Molecular Pathology. 141. 104956–104956. 1 indexed citations
2.
Kaur, Prabhjot, et al.. (2025). Cerebral Venous Sinus Thrombosis: A Complication of Secondary Polycythemia From Testosterone Use. Cureus. 17(6). e85789–e85789.
3.
Kaur, Prabhjot, et al.. (2025). Erucin-loaded chitosan coated solid lipid hybrid nanoparticles: An efficient drug delivery system for enhancing solubility and sustained release. International Journal of Biological Macromolecules. 308(Pt 2). 142350–142350. 1 indexed citations
4.
Kaur, Prabhjot, et al.. (2025). Epiglottitis Caused by Pasteurella multocida: An Uncommon Presentation. Cureus. 17(3). e81365–e81365.
5.
Kaur, Prabhjot, et al.. (2024). Landmark Detection Using Convolutional Neural Network: A Review. Lecture notes in networks and systems. 157–172. 1 indexed citations
6.
Kaur, Prabhjot, et al.. (2024). Genome‐wide association study for powdery mildew resistance in CIMMYT 's spring wheat germplasm. Plant Pathology. 74(2). 455–464. 2 indexed citations
7.
Ravi, Vinayakumar, et al.. (2024). Plant Leaf Disease Detection and Classification Using Segmentation Encoder Techniques. The Open Agriculture Journal. 18(1). 8 indexed citations
8.
Kaur, Prabhjot, et al.. (2023). APPRISING THE CHANGE IN OCCUPANTS’ AND DESIGNERS’ APPROACH APROPOS SPATIAL LAYOUTS POST-COVID-19. ShodhKosh Journal of Visual and Performing Arts. 4(2SE).
9.
Kaur, Prabhjot, et al.. (2023). A Hybrid Approach to Identify Plant Leaf Disease using Machine Learning and Image Processing. International Journal of Computer Applications. 185(27). 25–30. 1 indexed citations
11.
Harnal, Shilpi, et al.. (2022). Bibliometric Mapping of Trends, Applications and Challenges of Artificial Intelligence in Smart Cities. ICST Transactions on Scalable Information Systems. e76–e76. 9 indexed citations
12.
Kaur, Prabhjot, Shilpi Harnal, Vinay Gautam, Mukund Pratap Singh, & Santar Pal Singh. (2022). A novel transfer deep learning method for detection and classification of plant leaf disease. Journal of Ambient Intelligence and Humanized Computing. 14(9). 12407–12424. 72 indexed citations
13.
Kaur, Prabhjot, Shilpi Harnal, Rajeev Tiwari, et al.. (2021). A Hybrid Convolutional Neural Network Model for Diagnosis of COVID-19 Using Chest X-ray Images. International Journal of Environmental Research and Public Health. 18(22). 12191–12191. 32 indexed citations
14.
Kaur, Prabhjot & Vinay Gautam. (2021). Plant Biotic Disease Identification and Classification Based on Leaf Image: A Review. Lecture notes in networks and systems. 597–610. 21 indexed citations
15.
Kaur, Prabhjot, Anil Kumar Sao, & Chirag Ahuja. (2021). Super Resolution of Magnetic Resonance Images. Journal of Imaging. 7(6). 101–101. 1 indexed citations
16.
Kaur, Prabhjot, et al.. (2020). Denture Identification Methods:A Review. Indian Journal of Public Health Research & Development. 11(1). 459–459.
17.
Kaur, Prabhjot, et al.. (2017). Modification of Vivaldi Tapered Slot Antenna with Square Shaped Slot. International Journal of Engineering Trends and Technology. 50(4). 230–233. 1 indexed citations
18.
Singh, Williamjeet & Prabhjot Kaur. (2016). Comparative Analysis of Classification Techniques for Predicting Computer Engineering Students’ Academic Performance. International Journal of Advanced Research in Computer Science. 7(6). 10 indexed citations
19.
Burchard, Paul R., Saurabh Malhotra, Prabhjot Kaur, & Gregory J. Tsongalis. (2013). Detection of the FCGR3a polymorphism using a real-time polymerase chain reaction assay. Cancer Genetics. 206(4). 130–134. 11 indexed citations
20.
Kaur, Prabhjot, et al.. (2011). Markovian Queuing Model for Dynamic Spectrum Allocation in Centralized Architecture for Cognitive Radios. International Journal of Engineering and Technology. 3(1). 96–101. 13 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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