A near real-time deep learning approach for detecting rice phenology based on UAV images

•Using CNN to detect rice phenology by a mono-temporal imagery of UAV was investigated.•Shape-model-fitting method underperformed with short length of time-series data.•Integrating regional mean thermal time into CNN improve the detection accuracy.•The estimated harvest dates was in close agreement with the observation.•The proposed approach provides near real-time estimation of the principal phenological stages of rice.