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Based on the search results, a is an intermediate representation of data—such as image pixels or text—learned automatically by a deep neural network, typically within its hidden layers, rather than being handcrafted by humans. These features are crucial for tasks like text spotting, computer vision, and crack segmentation. Key Aspects of Deep Features

Deep Features for Text Spotting - Oxford University Research Archive Rewrite_22-01-27_b8095833_Patch2.1

To tackle the issue of redundant features, a feature correlation loss function (FC-Loss) is used to encourage the network to learn more independent, effective features. Based on the search results, a is an

Reducing redundancy and improving model efficiency (e.g., in crack segmentation datasets like Crack2181). Reducing redundancy and improving model efficiency (e

I can also focus on how these features are used for a (e.g., CNN, Transformer).

Detecting and recognizing text within natural images.