Emerging artificial synaptic devices for neuromorphic computing
In today's era of big‐data, a new computing paradigm beyond today's von‐Neumann
architecture is needed to process these large‐scale datasets efficiently. Inspired by the …
architecture is needed to process these large‐scale datasets efficiently. Inspired by the …
Automated seizure prediction
In the past two decades, significant advances have been made on automated
electroencephalogram (EEG)-based diagnosis of epilepsy and seizure detection. A number …
electroencephalogram (EEG)-based diagnosis of epilepsy and seizure detection. A number …
Efficient training of physics‐informed neural networks via importance sampling
MA Nabian, RJ Gladstone… - Computer‐Aided Civil and …, 2021 - Wiley Online Library
Physics‐informed neural networks (PINNs) are a class of deep neural networks that are
trained, using automatic differentiation, to compute the response of systems governed by …
trained, using automatic differentiation, to compute the response of systems governed by …
Automatic pixel‐level crack detection and measurement using fully convolutional network
The spatial characteristics of cracks are significant indicators to assess and evaluate the
health of existing buildings and infrastructures. However, the current manual crack …
health of existing buildings and infrastructures. However, the current manual crack …
Towards a better understanding of transfer learning for medical imaging: a case study
Featured Application The proposed intelligent medical system is applicable for a medical
diagnostic system, especially for the diagnosis of diabetic foot ulcer. Abstract One of the …
diagnostic system, especially for the diagnosis of diabetic foot ulcer. Abstract One of the …
Automatic pixel‐level multiple damage detection of concrete structure using fully convolutional network
S Li, X Zhao, G Zhou - Computer‐Aided Civil and Infrastructure …, 2019 - Wiley Online Library
Deep learning‐based structural damage detection methods overcome the limitation of
inferior adaptability caused by extensively varying real‐world situations (eg, lighting and …
inferior adaptability caused by extensively varying real‐world situations (eg, lighting and …
Automated EEG-based screening of depression using deep convolutional neural network
In recent years, advanced neurocomputing and machine learning techniques have been
used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In …
used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In …
Image‐based post‐disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization
X Liang - Computer‐Aided Civil and Infrastructure Engineering, 2019 - Wiley Online Library
Many bridge structures, one of the most critical components in transportation infrastructure
systems, exhibit signs of deteriorations and are approaching or beyond the initial design …
systems, exhibit signs of deteriorations and are approaching or beyond the initial design …
Concrete bridge surface damage detection using a single‐stage detector
C Zhang, C Chang, M Jamshidi - Computer‐Aided Civil and …, 2020 - Wiley Online Library
Early and timely detection of surface damages is important for maintaining the functionality,
reliability, and safety of concrete bridges. Recent advancement in convolution neural …
reliability, and safety of concrete bridges. Recent advancement in convolution neural …
Autonomous UAVs for structural health monitoring using deep learning and an ultrasonic beacon system with geo‐tagging
Visual inspection has traditionally been used for structural health monitoring. However,
assessments conducted by trained inspectors or using contact sensors on structures for …
assessments conducted by trained inspectors or using contact sensors on structures for …