223 citations · 389 across the 45 of their papers we have counts for
6 papers · 2 filters
Pruning by Active Attention Manipulation
Zahra Babaiee, Lucas Liebenwein, Ramin Hasani +2
Filter pruning of a CNN is typically achieved by applying discrete masks on the CNN's filter weights or activation maps, post-training. Here, we present a new filter-importance-sco…
Are All Vision Models Created Equal? A Study of the Open-Loop to Closed-Loop Causality Gap
Mathias Lechner, Ramin Hasani, Alexander Amini +3
There is an ever-growing zoo of modern neural network models that can efficiently learn end-to-end control from visual observations. These advanced deep models, ranging from convol…
Deep Learning on Home Drone: Searching for the Optimal Architecture
Alaa Maalouf, Yotam Gurfinkel, Barak Diker +3
We suggest the first system that runs real-time semantic segmentation via deep learning on a weak micro-computer such as the Raspberry Pi Zero v2 (whose price was $15) attached to…
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
Zhijian Liu, Haotian Tang, Alexander Amini +4
Multi-sensor fusion is essential for an accurate and reliable autonomous driving system. Recent approaches are based on point-level fusion: augmenting the LiDAR point cloud with ca…
End-to-End Sensitivity-Based Filter Pruning
Zahra Babaiee, Lucas Liebenwein, Ramin Hasani +2
In this paper, we present a novel sensitivity-based filter pruning algorithm (SbF-Pruner) to learn the importance scores of filters of each layer end-to-end. Our method learns the…
Concept Graph Neural Networks for Surgical Video Understanding
Yutong Ban, Jennifer A. Eckhoff, Thomas M. Ward +4
We constantly integrate our knowledge and understanding of the world to enhance our interpretation of what we see. This ability is crucial in application domains which entail reaso…