Structural coding: A low-cost scheme to protect cnns from large-granularity memory faults
The advent of High-Performance Computing has led to the adoption of Convolutional Neural
Networks (CNNs) in safety-critical applications such as autonomous vehicles. However …
Networks (CNNs) in safety-critical applications such as autonomous vehicles. However …
[HTML][HTML] Autonomous vehicles and urban traffic management for sustainability: Impacts of transition of control and dedicated lanes
ZB Yıldırım, M Özuysal - Sustainability, 2024 - mdpi.com
Autonomous vehicles (AVs) are increasingly recognized for their potential to enhance urban
traffic systems, particularly in traffic management and sustainability. This study explores AV …
traffic systems, particularly in traffic management and sustainability. This study explores AV …
Road traffic safety assessment in self-driving vehicles based on time-to-collision with motion orientation
Traffic conflict analysis based on Surrogate Safety Measures (SSMs) helps to estimate the
risk level of an ego-vehicle interacting with other road users. Nonetheless, risk assessment …
risk level of an ego-vehicle interacting with other road users. Nonetheless, risk assessment …
Real-Time Collision Mitigation Strategies for Autonomous Vehicles
L Bosia, L Manganotto, M Anghileri… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Autonomous vehicles (AVs) offer a promising solution to mitigate human errors and,
consequently, reduce the number of road traffic fatalities. While AVs may significantly reduce …
consequently, reduce the number of road traffic fatalities. While AVs may significantly reduce …
Structural coding: a low-cost scheme to protect CNNs from large-granularity memory errors
A Asgari Khoshouyeh - 2022 - open.library.ubc.ca
Abstract Convolutional Neural Networks (CNNs) are broadly used in safety-critical
applications such as autonomous vehicles. While demonstrating high accuracy, CNN …
applications such as autonomous vehicles. While demonstrating high accuracy, CNN …