Human visual perception almost always outperforms computer image processing algorithms. For example, your brain knows a river when it sees one. But a computer can’t distinguish rivers from lakes, roads, or sewage treatment plants.
Especially with the spatially extreme and spectrally minimal resolution UAV image data, a change in thinking must take place. It makes more sense to think in terms of objects or entities to be identified rather than classifying them in terms of individual pixels. The basic principle of object-based image analysis (OBIA) is to segment first and then classify.
The segmentation process is algorithm-dependent but looks iteratively for similarities in space, structure, and channel dimensions for grouping neighboring and similar pixels into objects. These segments are classified in the next step using supervised training data.
For all who prefer the workflow as video.