Classification and Protection of Critical Weights in CNNs
DescriptionConvolutional neural networks (CNNs) are being incorporated into many image-based tasks across a variety of domains. Some of these tasks are real-world safety critical tasks such as object detection and lane line detection for self-driving cars. These applications have strict safety requirements and must be able guarantee the reliable operation of the network. We propose a selective triplication of important parts of the network determined via weight pruning methodologies in order to maintain a reliable CNN in environments that may be resource-limited.
Event Type
Workshop
TimeSunday, 13 November 20221:40pm - 1:44pm CST
LocationC148
W
Diversity Equity Inclusion (DEI)
Education and Training and Outreach
Recorded