Neural Architecture Search

DenseNAS is a neural architecture search method that utilises a densely connected search space. The search space is represented as a dense super network, which is built upon designed routing blocks. In the super network, routing blocks are densely connected and we search for the best path between them to derive the final architecture. A chained cost estimation algorithm is used to approximate the model cost during the search.

Source: Densely Connected Search Space for More Flexible Neural Architecture Search

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Image Classification 1 100.00%

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🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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