# Jie Deng

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/jie-deng-2/

## Facts

| Field | Value |
| --- | --- |
| Citations | 988 |
| Field | Remote Sensing in Agriculture |
| h-index | 12 |
| i10-index | 15 |
| Last Known Institution | Xiamen University |
| OpenAlex ID | https://openalex.org/A5101454577 |
| ORCID iD | 0000-0002-2391-0782 |
| Works | 50 |

## Researcher papers

- [Classifying EEG-based motor imagery tasks by means of time–frequency synthesized spatial patterns](https://scholariq.org/papers/classifying-eeg-based-motor-imagery-tasks-by-means-of-time-frequency-synthesized/)
- [A large-scale hierarchical image database](https://scholariq.org/papers/a-large-scale-hierarchical-image-database/)
- [BBO-BPNN and AMPSO-BPNN for multiple-criteria inventory classification](https://scholariq.org/papers/bbo-bpnn-and-ampso-bpnn-for-multiple-criteria-inventory-classification/)
- [Image segmentation encryption algorithm with chaotic sequence generation participated by cipher and multi-feedback loops](https://scholariq.org/papers/image-segmentation-encryption-algorithm-with-chaotic-sequence-generation/)
- [RustQNet: Multimodal deep learning for quantitative inversion of wheat stripe rust disease index](https://scholariq.org/papers/rustqnet-multimodal-deep-learning-for-quantitative-inversion-of-wheat-stripe/)
- [Applying convolutional neural networks for detecting wheat stripe rust transmission centers under complex field conditions using RGB-based high spatial resolution images from UAVs](https://scholariq.org/papers/applying-convolutional-neural-networks-for-detecting-wheat-stripe-rust/)
- [Pixel-level regression for UAV hyperspectral images: Deep learning-based quantitative inverse of wheat stripe rust disease index](https://scholariq.org/papers/pixel-level-regression-for-uav-hyperspectral-images-deep-learning-based/)
- [EEG-based classification for elbow versus shoulder torque intentions involving stroke subjects](https://scholariq.org/papers/eeg-based-classification-for-elbow-versus-shoulder-torque-intentions-involving/)
- [A Survey of Sample-Efficient Deep Learning for Change Detection in Remote Sensing: Tasks, strategies, and challenges](https://scholariq.org/papers/a-survey-of-sample-efficient-deep-learning-for-change-detection-in-remote/)
- [Automated Tumor Segmentation in Radiotherapy](https://scholariq.org/papers/automated-tumor-segmentation-in-radiotherapy/)

## Researcher topics

- [Remote Sensing in Agriculture](https://scholariq.org/topics/remote-sensing-in-agriculture/)
- [Smart Agriculture and AI](https://scholariq.org/topics/smart-agriculture-and-ai/)
- [Wheat and Barley Genetics and Pathology](https://scholariq.org/topics/wheat-and-barley-genetics-and-pathology/)
- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)
- [Spectroscopy and Chemometric Analyses](https://scholariq.org/topics/spectroscopy-and-chemometric-analyses/)

## Researcher university

- [Xiamen University](https://scholariq.org/institutions/xiamen-university/)

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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.