Edna C. Too

1.4k total citations · 1 hit paper
11 papers, 922 citations indexed

About

Edna C. Too is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Plant Science. According to data from OpenAlex, Edna C. Too has authored 11 papers receiving a total of 922 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 4 papers in Plant Science. Recurrent topics in Edna C. Too's work include Smart Agriculture and AI (4 papers), Advanced Neural Network Applications (4 papers) and Neural Networks and Applications (2 papers). Edna C. Too is often cited by papers focused on Smart Agriculture and AI (4 papers), Advanced Neural Network Applications (4 papers) and Neural Networks and Applications (2 papers). Edna C. Too collaborates with scholars based in Kenya and China. Edna C. Too's co-authors include Yujian Li, Yingchun Liu, Benson Kipkemboi Kenduiywo, Pius Kwao Gadosey, Zhaoying Liu, Jianbiao Zhang and Ting Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers and Electronics in Agriculture and Journal of Intelligent & Fuzzy Systems.

In The Last Decade

Edna C. Too

10 papers receiving 855 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A comparative study of fine-tuning deep learning models for plant disease identification

2018 816 citations Edna C. Too, Yujian Li et al. Computers and Electronics in Agriculture profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Edna C. Too Kenya	5	756	290	168	65	60	11	922
Yuandong Sun China	7	712 0.9×	291 1.0×	130 0.8×	80 1.2×	40 0.7×	13	897
Aravind Krishnaswamy Rangarajan India	10	616 0.8×	306 1.1×	109 0.6×	53 0.8×	58 1.0×	14	786
J. Arun Pandian India	9	772 1.0×	280 1.0×	115 0.7×	54 0.8×	63 1.1×	32	917
Vinay Gautam India	14	595 0.8×	211 0.7×	89 0.5×	77 1.2×	97 1.6×	90	881
Mónica G. Larese Argentina	6	664 0.9×	251 0.9×	192 1.1×	96 1.5×	40 0.7×	12	808
V. K. Singh India	10	1.1k 1.4×	446 1.5×	186 1.1×	67 1.0×	39 0.7×	43	1.2k
Sue Han Lee Malaysia	7	727 1.0×	295 1.0×	178 1.1×	66 1.0×	34 0.6×	15	860
Jone Echazarra Spain	5	774 1.0×	331 1.1×	173 1.0×	33 0.5×	25 0.4×	8	851
Emine Uçar Türkiye	7	482 0.6×	187 0.6×	75 0.4×	59 0.9×	95 1.6×	16	761

Countries citing papers authored by Edna C. Too

Since Specialization

Citations

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

Fields of papers citing papers by Edna C. Too

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edna C. Too. 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 Edna C. Too. The network helps show where Edna C. Too may publish in the future.

Co-authorship network of co-authors of Edna C. Too

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

All Works

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11 of 11 papers shown

1.

Too, Edna C., et al.. (2024). An X-ray image-based pruned dense convolution neural network for tuberculosis detection. SHILAP Revista de lepidopterología. 6. 100169–100169. 1 indexed citations

2.

Too, Edna C.. (2023). LightNet: pruned sparsed convolution neural network for image classification. International Journal of Computational Science and Engineering. 26(3). 283–295. 1 indexed citations

3.

Kenduiywo, Benson Kipkemboi, et al.. (2021). Arabica coffee leaf images dataset for coffee leaf disease detection and classification. SHILAP Revista de lepidopterología. 36. 107142–107142. 42 indexed citations

4.

Kenduiywo, Benson Kipkemboi, et al.. (2021). The Effect of Adaptive Learning Rate on the Accuracy of Neural Networks. International Journal of Advanced Computer Science and Applications. 12(8). 23 indexed citations

5.

Too, Edna C., et al.. (2020). Performance analysis of nonlinear activation function in convolution neural network for image classification. International Journal of Computational Science and Engineering. 21(4). 522–522. 17 indexed citations

6.

Gadosey, Pius Kwao, et al.. (2020). Performance analysis of nonlinear activation function in convolution neural network for image classification. International Journal of Computational Science and Engineering. 21(4). 522–522. 2 indexed citations

7.

Gadosey, Pius Kwao, et al.. (2020). SEB-Net. 542–551.

8.

Too, Edna C., et al.. (2019). The Convolution Neural Network with Transformed Exponential Linear Unit Activation Function for Image Classification. 55–62. 2 indexed citations

9.

Too, Edna C., et al.. (2019). Deep pruned nets for efficient image-based plants disease classification. Journal of Intelligent & Fuzzy Systems. 37(3). 4003–4019. 17 indexed citations

10.

Too, Edna C., et al.. (2018). A comparative study of fine-tuning deep learning models for plant disease identification. Computers and Electronics in Agriculture. 161. 272–279. 816 indexed citations breakdown →

11.

Zhang, Jianbiao, et al.. (2018). An Evaluation on Securing Cloud Systems based on Cryptographic Key Algorithms. 14–20. 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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