We present a state-of-the-art image recognition system, Deep Image, developed using endto-end deep learning. The key components are a custom-built supercomputer dedicated to deep learning, a highly optimized parallel algorithm using new strategies for data partitioning and communication, larger deep neural network models, novel data augmentation approaches, and usage of multi-scale high-resolution images. On one of the most challenging computer vision benchmarks, the ImageNet classification challenge, our system has achieved the best result to date, with a top-5 error rate of 5.33%, a relative 20.0% improvement over the previous best result.
Deep Image REF is a custom-built supercomputer for deep learning via GPUs.
Deep Image: Scaling up Image Recognition
ArXiv
ArXiv
Computer Science