# Sue Han Lee

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/sue-han-lee/

## Facts

| Field | Value |
| --- | --- |
| Citations | 1,373 |
| Field | Smart Agriculture and AI |
| h-index | 10 |
| i10-index | 10 |
| Last Known Institution | Swinburne University of Technology Sarawak Campus |
| OpenAlex ID | https://openalex.org/A5026356758 |
| ORCID iD | 0000-0003-1767-9307 |
| Works | 29 |

## Researcher papers

- [How deep learning extracts and learns leaf features for plant classification](https://scholariq.org/papers/how-deep-learning-extracts-and-learns-leaf-features-for-plant-classification/)
- [New perspectives on plant disease characterization based on deep learning](https://scholariq.org/papers/new-perspectives-on-plant-disease-characterization-based-on-deep-learning/)
- [Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks](https://scholariq.org/papers/multi-organ-plant-classification-based-on-convolutional-and-recurrent-neural/)
- [Attention-Based Recurrent Neural Network for Plant Disease Classification](https://scholariq.org/papers/attention-based-recurrent-neural-network-for-plant-disease-classification/)
- [Deep-plant: Plant identification with convolutional neural networks](https://scholariq.org/papers/deep-plant-plant-identification-with-convolutional-neural-networks/)
- [Plant Identification System based on a Convolutional Neural Network for the LifeClef 2016 Plant Classification Task.](https://scholariq.org/papers/plant-identification-system-based-on-a-convolutional-neural-network-for-the/)
- [A machine learning approach for cross-domain plant identification using herbarium specimens](https://scholariq.org/papers/a-machine-learning-approach-for-cross-domain-plant-identification-using/)
- [Conditional Multi-Task learning for Plant Disease Identification](https://scholariq.org/papers/conditional-multi-task-learning-for-plant-disease-identification/)
- [Beyond supervision: Harnessing self-supervised learning in unseen plant disease recognition](https://scholariq.org/papers/beyond-supervision-harnessing-self-supervised-learning-in-unseen-plant-disease/)
- [HGO-CNN: Hybrid generic-organ convolutional neural network for multi-organ plant classification](https://scholariq.org/papers/hgo-cnn-hybrid-generic-organ-convolutional-neural-network-for-multi-organ-plant/)

## Researcher topics

- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)
- [Plant Virus Research Studies](https://scholariq.org/topics/plant-virus-research-studies/)
- [Biological and pharmacological studies of plants](https://scholariq.org/topics/biological-and-pharmacological-studies-of-plants/)
- [Plant Pathogens and Fungal Diseases](https://scholariq.org/topics/plant-pathogens-and-fungal-diseases/)

## Researcher university

- [Swinburne University of Technology Sarawak Campus](https://scholariq.org/institutions/swinburne-university-of-technology-sarawak-campus/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.