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08/16/2023
Contrastive Learning for Lane Detection via cross-similarity
Detecting road lanes is challenging due to intricate markings vulnerable...
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06/16/2023
Enhancing Fault Resilience of QNNs by Selective Neuron Splitting
The superior performance of Deep Neural Networks (DNNs) has led to their...
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05/31/2023
Special Session: Approximation and Fault Resiliency of DNN Accelerators
Deep Learning, and in particular, Deep Neural Network (DNN) is nowadays ...
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05/31/2023
APPRAISER: DNN Fault Resilience Analysis Employing Approximation Errors
Nowadays, the extensive exploitation of Deep Neural Networks (DNNs) in s...
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05/09/2023
A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networks
Artificial Intelligence (AI) and, in particular, Machine Learning (ML) h...
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03/14/2023
DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators
While the role of Deep Neural Networks (DNNs) in a wide range of safety-...
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03/13/2023
DeepVigor: Vulnerability Value Ranges and Factors for DNNs' Reliability Assessment
Deep Neural Networks (DNNs) and their accelerators are being deployed ev...
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02/11/2023
Auto-SpMV: Automated Optimizing SpMV Kernels on GPU
Sparse matrix-vector multiplication (SpMV) is an essential linear algebr...
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12/08/2022
GTFLAT: Game Theory Based Add-On For Empowering Federated Learning Aggregation Techniques
GTFLAT, as a game theory-based add-on, addresses an important research q...
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07/14/2022
PR-DARTS: Pruning-Based Differentiable Architecture Search
The deployment of Convolutional Neural Networks (CNNs) on edge devices i...
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04/21/2020
NOM: Network-On-Memory for Inter-Bank Data Transfer in Highly-Banked Memories
Data copy is a widely-used memory operation in many programs and operati...
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04/19/2020
Multi-level Binarized LSTM in EEG Classification for Wearable Devices
Long Short-Term Memory (LSTM) is widely used in various sequential appli...
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04/19/2020
MuBiNN: Multi-Level Binarized Recurrent Neural Network for EEG signal Classification
Recurrent Neural Networks (RNN) are widely used for learning sequences i...
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02/05/2016
