Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A systematic literature review on hardware reliability assessment methods for deep neural networks
Artificial Intelligence (AI) and, in particular, Machine Learning (ML), have emerged to be
utilized in various applications due to their capability to learn how to solve complex …
utilized in various applications due to their capability to learn how to solve complex …
Artificial neural networks for space and safety-critical applications: Reliability issues and potential solutions
Machine learning is among the greatest advancements in computer science and
engineering and is today used to classify or detect objects, a key feature in autonomous …
engineering and is today used to classify or detect objects, a key feature in autonomous …
Assessing convolutional neural networks reliability through statistical fault injections
Assessing the reliability of modern devices running CNN algorithms is a very difficult task.
Actually, the complexity of the state-of-the-art devices makes exhaustive Fault Injection (FI) …
Actually, the complexity of the state-of-the-art devices makes exhaustive Fault Injection (FI) …
A survey on deep learning resilience assessment methodologies
Deep learning (DL) reliability is becoming a growing concern, and efficient reliability
assessment approaches are required to meet safety constraints. This article presents a …
assessment approaches are required to meet safety constraints. This article presents a …
[HTML][HTML] A comprehensive review and a taxonomy of edge machine learning: Requirements, paradigms, and techniques
The union of Edge Computing (EC) and Artificial Intelligence (AI) has brought forward the
Edge AI concept to provide intelligent solutions close to the end-user environment, for …
Edge AI concept to provide intelligent solutions close to the end-user environment, for …
Impact of high-level-synthesis on reliability of artificial neural network hardware accelerators
Dedicated hardware is required to efficiently execute the highly resource-demanding
modern artificial neural networks (ANNs). The high complexity of ANN systems has …
modern artificial neural networks (ANNs). The high complexity of ANN systems has …
[HTML][HTML] Evaluating single event upsets in deep neural networks for semantic segmentation: An embedded system perspective
As the deployment of artificial intelligence (AI) algorithms at edge devices becomes
increasingly prevalent, enhancing the robustness and reliability of autonomous AI-based …
increasingly prevalent, enhancing the robustness and reliability of autonomous AI-based …
Selective hardening of critical neurons in deep neural networks
In the literature, it is argued that Deep Neural Networks (DNNs) possess a certain degree of
robustness mainly for two reasons: their distributed and parallel architecture, and their …
robustness mainly for two reasons: their distributed and parallel architecture, and their …
Sci-fi: a smart, accurate and unintrusive fault-injector for deep neural networks
In recent years, the reliability of Deep Neural Networks (DNN) has become the focus of an
increasing number of research activities. In particular, researchers have focused on …
increasing number of research activities. In particular, researchers have focused on …
[HTML][HTML] Gated-CNN: Combating NBTI and HCI aging effects in on-chip activation memories of Convolutional Neural Network accelerators
Abstract Negative Bias Temperature Instability (NBTI) and Hot Carrier Injection (HCI) are two
of the main reliability threats in current technology nodes. These aging phenomena degrade …
of the main reliability threats in current technology nodes. These aging phenomena degrade …