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06/10/2023
Fault Localization for Framework Conversions of Image Recognition Models
When deploying Deep Neural Networks (DNNs), developers often convert mod...
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06/05/2023
A Differential Testing Framework to Evaluate Image Recognition Model Robustness
Image recognition tasks typically use deep learning and require enormous...
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06/02/2023
MutateNN: Mutation Testing of Image Recognition Models Deployed on Hardware Accelerators
With the research advancement of Artificial Intelligence in the last yea...
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11/01/2022
Exploring Effects of Computational Parameter Changes to Image Recognition Systems
Image recognition tasks typically use deep learning and require enormous...
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06/19/2022
Productive Reproducible Workflows for DNNs: A Case Study for Industrial Defect Detection
As Deep Neural Networks (DNNs) have become an increasingly ubiquitous wo...
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04/26/2022
Bifrost: End-to-End Evaluation and Optimization of Reconfigurable DNN Accelerators
Reconfigurable accelerators for deep neural networks (DNNs) promise to i...
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01/14/2022
Transfer-Tuning: Reusing Auto-Schedules for Efficient Tensor Program Code Generation
Auto-scheduling for tensor programs is a process where a search algorith...
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10/01/2021
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference
Edge computing devices inherently face tight resource constraints, which...
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07/24/2020
Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference
Optimising deep learning inference across edge devices and optimisation ...
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06/17/2020
