MobileNetV3 is the third generation MobileNet, co-designed by neural architecture search and human expertise — combining NAS-discovered architecture (MnasNet) with manual refinements including SE attention, h-swish activation, and an efficient last stage.

What Is MobileNetV3?

• NAS + Manual: Architecture search finds the block structure. Human experts refine the initial/final layers.
• h-swish: $ ext{h-swish}(x) = x cdot ext{ReLU6}(x+3)/6$ — efficient approximation of Swish for mobile.
• SE Blocks: Squeeze-and-Excitation attention in selected blocks.
• Two Variants: MobileNetV3-Large (compute-intensive tasks), MobileNetV3-Small (extreme efficiency).
• Paper: Howard et al. (2019).

Why It Matters

• SOTA Mobile Accuracy: Best accuracy-efficiency trade-off for mobile deployment at time of release.
• Production: Default backbone in many Google mobile ML products (Pixel phones, Lens).
• Human-NAS Symbiosis: Demonstrated that combining NAS with human intuition outperforms either alone.

MobileNetV3 is NAS meets human engineering — the optimal mobile architecture discovered through human-machine collaboration.