MnasNet: Platform-Aware Neural Architecture Search for Mobile

Designing convolutional neural networks (CNN) for mobile devices is challenging because mobile models need to be small and fast, yet still accurate. Although significant efforts have been dedicated to design and improve mobile CNNs on all dimensions, it is very difficult to manually balance these trade-offs when there are so many architectural possibilities to consider.

Data and Resources

Cite this as

Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le (2024). Dataset: MnasNet: Platform-Aware Neural Architecture Search for Mobile. https://doi.org/10.57702/mhfa6deb

DOI retrieved: December 3, 2024

Additional Info

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Created December 3, 2024
Last update December 3, 2024
Author Mingxing Tan
More Authors
Bo Chen
Ruoming Pang
Vijay Vasudevan
Mark Sandler
Andrew Howard
Quoc V. Le
Homepage https://github.com/tensorflow/tpu/tree/master/models/official/mnasnet