Sue Han Lee

1.3k citations
15 papers · 860 indexed · 2 hit papers · h-index 7
Topics
Smart Agriculture and AI (12 papers)Remote Sensing in Agriculture (6 papers)Plant Virus Research Studies (5 papers)
Partner nations
MalaysiaFranceItaly

In The Last Decade

Sue Han Lee

14 papers receiving 797 citations

Hit Papers

How deep learning extracts and learns leaf features for p...201720262020202320172020100200300400

Peers

Sue Han Lee
Comparison fields: 5 of 82
  • Plant Science 727
  • Analytical Chemistry 295
  • Ecology 178
  • Computer Vision and Pattern Recognition 66
  • Molecular Biology 35
Replace Mónica G. Larese with:
Mónica G. Larese Argentina
Henrik Skov Midtiby Denmark
Edna C. Too Kenya
Qiao-Liang Xiang Singapore
Keming Du China
Muhammad Hammad Saleem New Zealand
Sun Zhong-fu China
Ranjan Parekh India
Gercina Gonçalves da Silva Brazil
James Cope United Kingdom
Sue Han Lee relative to Mónica G. Larese Argentina Mónica G. Larese's profile →
Citations per field
00.5×2.5×
Mónica G. Larese · 1×
Citations per year

Countries citing papers authored by Sue Han Lee

Since Specialization
Citations

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

Fields of papers citing papers by Sue Han Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sue Han Lee. 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 Sue Han Lee. The network helps show where Sue Han Lee may publish in the future.

Co-authorship network of co-authors of Sue Han Lee

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

All Works

15 of 15 papers shown
#WorkIndexed citations
1 3
2 0
3 6
4 3
5 2
6 1
7 1
8 26
9 60
10
New perspectives on plant disease characterization based on deep learningbreakdown →
226
11 79
12
LifeClef 2017 Plant Identification Challenge: Classifying Plants using Generic-Organ Correlation Features.
2
13 12
14
How deep learning extracts and learns leaf features for plant classificationbreakdown →
415
15
Plant Identification System based on a Convolutional Neural Network for the LifeClef 2016 Plant Classification Task.
24

About Sue Han Lee

Sue Han Lee is a scholar working on Biophysics, Plant Science and Ecology, having authored 15 papers that have together received 860 indexed citations. Recurring topics across this work include Smart Agriculture and AI (12 papers), Remote Sensing in Agriculture (6 papers) and Plant Virus Research Studies (5 papers). The work is most often cited by research in Analytical Chemistry (295 citations), Plant Science (727 citations) and Ecology (178 citations). Sue Han Lee has collaborated with scholars based in Malaysia, France and Italy. Frequent co-authors include Chee Seng Chan, Paolo Remagnino, Simon Joseph Mayo, Alexis Joly, Pierre Bonnet, Hervé Goëau, Dongming Zhang, Chung Siung Choo, Dominic Ek Leong Ong and Patrick Then. Their work appears in journals such as IEEE Transactions on Image Processing, Frontiers in Plant Science and Pattern Recognition.

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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