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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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04/25/2023
Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks
Reducing the memory footprint of Machine Learning (ML) models, particula...
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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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10/11/2021
Algebraic and Puiseux series solutions of systems of autonomous algebraic ODEs of dimension one in several variables
In this paper we study systems of autonomous algebraic ODEs in several d...
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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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07/08/2021
Optimizing Data Processing in Space for Object Detection in Satellite Imagery
There is a proliferation in the number of satellites launched each year,...
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03/05/2021
Puiseux Series and Algebraic Solutions of First Order Autonomous AODEs – A MAPLE Package
There exist several methods for computing exact solutions of algebraic d...
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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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07/21/2020
Accelerating Deep Learning Applications in Space
Computing at the edge offers intriguing possibilities for the developmen...
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06/17/2020
Optimizing Grouped Convolutions on Edge Devices
When deploying a deep neural network on constrained hardware, it is poss...
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02/20/2020
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs
Convolutional Neural Networks (CNN) are becoming a common presence in ma...
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10/24/2018
HAKD: Hardware Aware Knowledge Distillation
Despite recent developments, deploying deep neural networks on resource ...
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10/24/2018
Distilling with Performance Enhanced Students
The task of accelerating large neural networks on general purpose hardwa...
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09/19/2018