articleJun 1, 2023Closed access
MobileOne: An Improved One millisecond Mobile Backbone
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Abstract
Efficient neural network backbones for mobile devices are often optimized for metrics such as FLOPs or parameter count. However, these metrics may not correlate well with latency of the network when deployed on a mobile device. Therefore, we perform extensive analysis of different metrics by deploying several mobile-friendly networks on a mobile device. We identify and analyze architectural and optimization bottlenecks in recent efficient neural networks and provide ways to mitigate these bottlenecks. To this end, we design an efficient backbone MobileOne, with variants achieving an inference time under 1 ms on an iPhone12 with 75.9% top-1 accuracy on ImageNet. We show that MobileOne achieves state-of-the-art…
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Topics
Keywords
- Computer science
- Latency (audio)
- Inference
- Mobile device
- FLOPS
- Millisecond
- Segmentation
- Artificial neural network
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