From Hashing to CNNs: Training BinaryWeight Networks via Hashing

Understand

Deep convolutional neural networks (CNNs) have shown appealing performance on various computer vision tasks in recent years.

• This motivates people to deploy CNNs to realworld applications.
• However, most of state-of-art CNNs require large memory and computational resources, which hinders the deployment on mobile devices.
• Recent studies show that low-bit weight representation can reduce much storage and memory demand, and also can achieve efficient network inference.