most citedAn Automotive Case Study on the Limits of Approximation for Object Detection

7 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AR2023

SafeTI Traffic Injector Enhancement for Effective Interference Testing in Critical Real-Time Systems

Francisco Fuentes, Raimon Casanova, Sergi Alcaide +1

Safety-critical domains, such as automotive, space, and robotics, are adopting increasingly powerful multicores with abundant hardware shared resources for higher performance and e…

cs.AR2023

SafeLS: Toward Building a Lockstep NOEL-V Core

Marcel Sarraseca, Sergi Alcaide, Francisco Fuentes +6

Safety-critical systems such as those in automotive, avionics and space, require appropriate safety measures to avoid silent data corruption upon random hardware errors such as tho…

cs.AR20231 cited

Envisioning a Safety Island to Enable HPC Devices in Safety-Critical Domains

Jaume Abella, Francisco J. Cazorla, Sergi Alcaide +3

HPC (High Performance Computing) devices increasingly become the only alternative to deliver the performance needed in safety-critical autonomous systems (e.g., autonomous cars, un…

cs.AR20237 cited

An Automotive Case Study on the Limits of Approximation for Object Detection

Martí Caro, Hamid Tabani, Jaume Abella +9

The accuracy of camera-based object detection (CBOD) built upon deep learning is often evaluated against the real objects in frames only. However, such simplistic evaluation ignore…

cs.AR20236 cited

At-Scale Evaluation of Weight Clustering to Enable Energy-Efficient Object Detection

Martí Caro, Hamid Tabani, Jaume Abella

Accelerators implementing Deep Neural Networks for image-based object detection operate on large volumes of data due to fetching images and neural network parameters, especially if…