Source-Specific Features Can Consume Model Capacity
When images come from a different source, a capacity-limited network may devote representational resources to source-specific patterns, such as uniform backgrounds or different camera angles. If those patterns differ substantially from the target data and do not help the target task, the model may have less capacity for target-relevant features, potentially reducing target performance.
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