Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Adapting a Globally-Trained Plant Identification Model for Multi-Species Detection of Invasive Alien Plants in Roadside Imagery
Saved in:
| Published in: | Biodiversity Information Science and Standards |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
Similar Items: Adapting a Globally-Trained Plant Identification Model for Multi-Species Detection of Invasive Alien Plants in Roadside Imagery
- Evaluating machine learning models for multi‐species wildlife detection and identification on remote sensed nadir imagery in South African savanna
- Early Assessment of the Invasiveness of the Alien Plant Vernonia amygdalina Del. Introduced in China
- Quantitative abundance and distribution data from the first systematic survey of alien invasive plants in the Xiaoxing'an Mountains, China (2022–2023)
- Community perceptions and management of the fleshy‐fruited invasive alien plant Pyracantha angustifolia: Insights from South Africa's Montane grasslands
- PlantCLEF 2025: Advancing AI-based Multi-Species Plant Identification in Vegetation Quadrats for Supporting Environmental Law and Biodiversity Monitoring
- A FAIR and Open Approach for the Study and Integrated Management of Invasive Alien Species in Italy