One potential limitation of the cosine similarity-based approach for uncertainty estimation is its sensitivity to variations in lighting conditions, viewpoints, and image quality. In scenes with complex lighting or occlusions, the cosine similarity may not accurately capture the similarity between feature embeddings. To address this limitation, alternative techniques such as using learned distance metrics or incorporating attention mechanisms to focus on relevant features could be explored. Additionally, ensemble methods that combine multiple similarity metrics or uncertainty estimation models could enhance the robustness of the approach.