Update README.md

README.md

@@ -146,10 +146,13 @@ The training curve shows steady learning, but performance plateaus due to datase
 
 ![Failure Example](./failure_example.png)
 
-This example shows a missed detection of a cyclist. This likely occurs due to:
-- small object size  
-- occlusion  
-- lack of sufficient training examples  
+This image shows two types of errors made by the model.
+
+In the first image, the model incorrectly detects a **vehicle** where there is actually part of a building. This is likely because the building has visual features (such as rectangular shapes and edges) that resemble vehicles in the training data.
+
+The second model identifies a **bike lane** where the road marking appears to be a bus lane. This suggests that the model has difficulty distinguishing between different types of lane markings, especially when they share similar visual patterns.
+
+These errors highlight an important limitation: the model relies heavily on visual similarity rather than deeper contextual understanding. Because the dataset contains limited variation and strong class imbalance, the model may generalize incorrectly when encountering unfamiliar or ambiguous scenes.
 
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