Machine learning techniques for diagnosis of alzheimer disease, mild cognitive disorder, and other types of dementia
Alzheimer's disease (AD) is one of the most common form of dementia which mostly affects
elderly people. AD identification in early stages is a difficult task in medical practice and …
elderly people. AD identification in early stages is a difficult task in medical practice and …
Self-supervised learning for electroencephalography
Decades of research have shown machine learning superiority in discovering highly
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
Cross‐scene pavement distress detection by a novel transfer learning framework
Deep learning has achieved promising results in pavement distress detection. However, the
training model's effectiveness varies according to the data and scenarios acquired by …
training model's effectiveness varies according to the data and scenarios acquired by …
[HTML][HTML] Uncertainty-driven ensembles of multi-scale deep architectures for image classification
The use of automatic systems for medical image classification has revolutionized the
diagnosis of a high number of diseases. These alternatives, which are usually based on …
diagnosis of a high number of diseases. These alternatives, which are usually based on …
Uncertainty-guided voxel-level supervised contrastive learning for semi-supervised medical image segmentation
Semi-supervised learning reduces overfitting and facilitates medical image segmentation by
regularizing the learning of limited well-annotated data with the knowledge provided by a …
regularizing the learning of limited well-annotated data with the knowledge provided by a …
A night pavement crack detection method based on image‐to‐image translation
C Liu, B Xu - Computer‐Aided Civil and Infrastructure …, 2022 - Wiley Online Library
Deep learning provides an efficient automated method for pavement condition surveys, but
the datasets used for this model are usually images taken in good lighting conditions. If …
the datasets used for this model are usually images taken in good lighting conditions. If …
Evolving deep learning convolutional neural networks for early COVID-19 detection in chest X-ray images
This article proposes a framework that automatically designs classifiers for the early
detection of COVID-19 from chest X-ray images. To do this, our approach repeatedly makes …
detection of COVID-19 from chest X-ray images. To do this, our approach repeatedly makes …
Detection of trees on street-view images using a convolutional neural network
Real-time detection of possible deforestation of urban landscapes is an essential task for
many urban forest monitoring services. Computational methods emerge as a rapid and …
many urban forest monitoring services. Computational methods emerge as a rapid and …
One-dimensional convolutional neural networks combined with channel selection strategy for seizure prediction using long-term intracranial EEG
Seizure prediction using intracranial electroencephalogram (iEEG) has attracted an
increasing attention during recent years. iEEG signals are commonly recorded in the form of …
increasing attention during recent years. iEEG signals are commonly recorded in the form of …
Machine learning in structural engineering
JP Amezquita-Sancheza… - Scientia …, 2020 - scientiairanica.sharif.edu
This article presents a review of selected articles about structural engineering applications of
machine learning (ML) in the past few years. It is divided into the following areas: structural …
machine learning (ML) in the past few years. It is divided into the following areas: structural …