Toward plant organs in nature: a new database for plant organ system
| Autor: | Guiqing He, Zhen Ao, Haixi Zhang, Yincheng Huo |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Database
Contextual image classification Computer science business.industry Deep learning ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology computer.software_genre Convolutional neural network Atomic and Molecular Physics and Optics Object detection Field (computer science) Computer Science Applications Visualization Data modeling 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing ComputingMethodologies_GENERAL Artificial intelligence Electrical and Electronic Engineering business computer Organ system |
| Zdroj: | Journal of Electronic Imaging. 29 |
| ISSN: | 1017-9909 |
| DOI: | 10.1117/1.jei.29.6.063009 |
| Popis: | The detection of plant organs is an important research field of plant recognition area. However, due to the lack of database of plant organs, the application of convolutional neural network-based object detection on plant species is very limited. A database of plant organs for deep learning-based object detection is constructed. A huge number of plant images are clawed using specific keywords through keyword search engines such as Baidu and Google. After that, an automatic junk image cleaning method is performed to remove junk images. Finally, artificial labeling is used to delineate plant organ regions. To evaluate the quality of the database, experiments in different object detection models are implemented. Results show that the established plant organ database has good performance in plant organs positioning and classification. |
| Databáze: | OpenAIRE |
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