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In the context of computer vision and image processing, a is an abstract representation of data learned by a neural network, specifically within the intermediate or "hidden" layers of a deep learning model. Key Characteristics

detect simple patterns like edges, textures, or blobs. Intermediate layers combine these into more complex shapes. 78E0C7C5-B8A7-4FE7-A739-9592B5DB499F.jpeg

represent high-level concepts or objects (e.g., a "wheel" or a "face"). In the context of computer vision and image

: Deep features are typically output as numerical vectors (a row of numbers) from the last fully connected or pooling layer before the final classification. Common Applications 78E0C7C5-B8A7-4FE7-A739-9592B5DB499F.jpeg