Enhancing PhenoCam Annotation Efficiency via Transfer Learning: Focus on Snow and Image Quality
Globally, automated ecological cameras (PhenoCam) are widely used to monitor vegetation and seasonal changes. Snow is usually easy to identify, but image quality flags (like haze, glare) can make it hard to detect in large datasets. Manual quality control becomes prohibitively time-intensive for large-scale phenological studies, creating a critical need for robust automated snow detection methods.
