Ternary Neural Networks for Resource-Efficient AI Applications

Understand

The computation and storage requirements for Deep Neural Networks (DNNs) are usually high.

• This issue limits their deployability on ubiquitous computing devices such as smart phones, wearables and autonomous drones.
• In this paper, we propose ternary neural networks (TNNs) in order to make deep learning more resource-efficient.
• We train these TNNs using a teacher-student approach based on a novel, layer-wise greedy methodology.