6.5k citations · 10.4k across the 118 of their papers we have counts for
3 papers · 2 filters
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…
Shallow Networks for High-Accuracy Road Object-Detection
Khalid Ashraf, Bichen Wu, Forrest N. Iandola +2
The ability to automatically detect other vehicles on the road is vital to the safety of partially-autonomous and fully-autonomous vehicles. Most of the high-accuracy techniques fo…
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
Forrest N. Iandola, Song Han, Matthew W. Moskewicz +3
Recent research on deep neural networks has focused primarily on improving accuracy. For a given accuracy level, it is typically possible to identify multiple DNN architectures tha…