Leisa Armstrong

1.2k total citations
62 papers, 785 citations indexed

About

Leisa Armstrong is a scholar working on Plant Science, Artificial Intelligence and Information Systems. According to data from OpenAlex, Leisa Armstrong has authored 62 papers receiving a total of 785 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Plant Science, 17 papers in Artificial Intelligence and 11 papers in Information Systems. Recurrent topics in Leisa Armstrong's work include Smart Agriculture and AI (15 papers), AI in cancer detection (10 papers) and Cell Image Analysis Techniques (7 papers). Leisa Armstrong is often cited by papers focused on Smart Agriculture and AI (15 papers), AI in cancer detection (10 papers) and Cell Image Analysis Techniques (7 papers). Leisa Armstrong collaborates with scholars based in Australia, India and Thailand. Leisa Armstrong's co-authors include Niketa Gandhi, Amiya Kumar Tripathy, Dean Diepeveen, Jinsong Leng, T. M. Shahriar Sazzad, Kathryn Williams, Dave Kendal, Craig Valli, David M. Cook and S. W. Adkins and has published in prestigious journals such as Australasian Journal of Paramedicine, Physiologia Plantarum and Environmental Monitoring and Assessment.

In The Last Decade

Leisa Armstrong

57 papers receiving 697 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Leisa Armstrong Australia 15 439 129 122 111 95 62 785
Niketa Gandhi India 13 298 0.7× 142 1.1× 78 0.6× 72 0.6× 109 1.1× 40 658
Rajni Jain India 16 336 0.8× 64 0.5× 117 1.0× 86 0.8× 42 0.4× 71 738
Zhaoyu Zhai China 10 373 0.8× 65 0.5× 65 0.5× 99 0.9× 58 0.6× 26 732
Dhivya Elavarasan India 7 556 1.3× 101 0.8× 132 1.1× 155 1.4× 49 0.5× 8 840
Nahina Islam Australia 11 386 0.9× 46 0.4× 72 0.6× 190 1.7× 40 0.4× 26 877
Vivek Sharma United States 19 500 1.1× 65 0.5× 104 0.9× 127 1.1× 20 0.2× 57 978
Yeni Herdiyeni Indonesia 17 357 0.8× 72 0.6× 200 1.6× 73 0.7× 64 0.7× 92 670
Andreas Kartakoullis Greece 7 367 0.8× 23 0.2× 78 0.6× 107 1.0× 46 0.5× 14 759
Naveed Iqbal Pakistan 10 410 0.9× 51 0.4× 59 0.5× 176 1.6× 42 0.4× 27 840
Borja Espejo-García Greece 15 540 1.2× 70 0.5× 124 1.0× 182 1.6× 31 0.3× 24 765

Countries citing papers authored by Leisa Armstrong

Since Specialization
Citations

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

Fields of papers citing papers by Leisa Armstrong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leisa Armstrong

This figure shows the co-authorship network connecting the top 25 collaborators of Leisa Armstrong. A scholar is included among the top collaborators of Leisa Armstrong 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 Leisa Armstrong. Leisa Armstrong 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
2.
Armstrong, Leisa, et al.. (2024). Application of Histopathology Image Analysis Using Deep Learning Networks. Australasian Journal of Paramedicine. 4(3). 417–436. 3 indexed citations
3.
Armstrong, Leisa, et al.. (2023). Association of farmers’ wellbeing in a drought-prone area, Thailand: applications of SPI and VCI indices. Environmental Monitoring and Assessment. 195(5). 612–612. 7 indexed citations
4.
Armstrong, Leisa, et al.. (2023). The segmentation of nuclei from histopathology images with synthetic data. Signal Image and Video Processing. 17(7). 3703–3711. 3 indexed citations
5.
Lee, Khui Hung, et al.. (2022). Exploring issues of resilience and technology use for older people - A scoping review protocol. Australasian Journal of Paramedicine. 11(15). e555111537773–e555111537773. 1 indexed citations
6.
Armstrong, Leisa, et al.. (2019). Detecting deviations from activities of daily living routines using kinect depth maps and power consumption data. Journal of Ambient Intelligence and Humanized Computing. 11(4). 1727–1747. 9 indexed citations
7.
Gandhi, Niketa & Leisa Armstrong. (2016). Applying data mining techniques to predict yield of rice in humid subtropical climatic zone of India. Australasian Journal of Paramedicine. 1901–1906. 21 indexed citations
8.
Armstrong, Leisa, et al.. (2016). Agricultural decision support framework for visualisation and prediction of Western Australian crop production. Australasian Journal of Paramedicine. 1907–1912. 4 indexed citations
9.
Sazzad, T. M. Shahriar, Leisa Armstrong, & Amiya Kumar Tripathy. (2016). Type P63 Non-counter Stained Digitized Color Images Performs Better Identification than Other Stains for Ovarian Tissue Analysis. Australasian Journal of Paramedicine. 15. 361–366. 4 indexed citations
10.
Gandhi, Niketa & Leisa Armstrong. (2016). Rice crop yield forecasting of tropical wet and dry climatic zone of India using data mining techniques. Australasian Journal of Paramedicine. 32 indexed citations
11.
Armstrong, Leisa, et al.. (2015). Factors influencing the use of information and communication technology (ICT) tools by the rural famers in Ratnagiri District of Maharashtra, India.. 5 indexed citations
12.
Armstrong, Leisa, et al.. (2014). On the application of genetic probabilistic neural network and cellular neural networks in precision agriculture. Murdoch Research Repository (Murdoch University). 6 indexed citations
13.
Armstrong, Leisa, et al.. (2014). Application of cellular neural networks and NaiveBayes classifier in agriculture. Australasian Journal of Paramedicine. 4 indexed citations
14.
Gandhi, Niketa, et al.. (2014). Mobile Applications for Indian Agriculture Sector: A case study. Australasian Journal of Paramedicine. 4 indexed citations
15.
Armstrong, Leisa, et al.. (2012). Use of Information and Communication Technology (ICT) Tools by Rural Farmers in Ratnagiri District of Maharastra, India. Australasian Journal of Paramedicine. 950–955. 6 indexed citations
16.
Armstrong, Leisa, et al.. (2010). Application of a data mining framework for the identification of agricultural production areas in WA. Australasian Journal of Paramedicine. 2 indexed citations
17.
Armstrong, Leisa, et al.. (2010). An eAgriculture-Based Decision Support Framework for Information Dissemination. International Journal of Human Capital and Information Technology Professionals. 1(4). 1–13. 5 indexed citations
18.
Armstrong, Leisa, et al.. (2007). Data mining can empower grower's crop decision making. Australasian Journal of Paramedicine. 1 indexed citations
19.
Armstrong, Leisa, et al.. (2007). The application of data mining techniques to characterize agricultural soil profiles. Australasian Journal of Paramedicine. 85–100. 24 indexed citations
20.
Ahmed, Sabbir & Leisa Armstrong. (2004). Securing Web Services with XML aware Digital Signatures.. 78(3). 129–134. 1 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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