activity
20152018
most citedSqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

93 citations · 210 across the 6 of their papers we have counts for

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Showing 2016Show all

2 papers · 1 filter

cs.CV2016★ 93 cited

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Bichen Wu, Alvin Wan, Forrest Iandola +2

Object detection is a crucial task for autonomous driving. In addition to requiring high accuracy to ensure safety, object detection for autonomous driving also requires real-time…

cs.LG2016★ 53 cited

How to scale distributed deep learning?

Peter H. Jin, Qiaochu Yuan, Forrest Iandola +1

Training time on large datasets for deep neural networks is the principal workflow bottleneck in a number of important applications of deep learning, such as object classification…