Medical image analysis
Apr 4, 2022
Deep learning has received extensive research interest in developing new medical image processing algorithms, and deep learning based models have been remarkably successful in a variety of medical imaging tasks to support disease detection and diagno...
Neural networks : the official journal of the International Neural Network Society
Apr 4, 2022
This paper mainly focuses on the lag H synchronization problem of coupled neural networks with multiple state or delayed state couplings. On one hand, by exploiting state feedback controller and Lyapunov functional, a criterion of lag H synchronizati...
Medical & biological engineering & computing
Apr 4, 2022
In this study, feature extraction methods used in the classification of single-channel lung sounds obtained by automatic identification of respiratory cycles were examined in detail in order to extract distinctive features at the lowest size. In this...
IET systems biology
Apr 4, 2022
Prenatal karyotype diagnosis is important to determine if the foetus has genetic diseases and some congenital diseases. Chromosome classification is an important part of karyotype analysis, and the task is tedious and lengthy. Chromosome classificati...
Communications biology
Apr 4, 2022
Bayesian networks (BNs) are disciplined, explainable Artificial Intelligence models that can describe structured joint probability spaces. In the context of understanding complex relations between a number of variables in biological settings, they ca...
Nature methods
Apr 4, 2022
The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimatio...
IEEE transactions on neural networks and learning systems
Apr 4, 2022
Recurrent neural networks (RNNs) have gained tremendous popularity in almost every sequence modeling task. Despite the effort, these kinds of discrete unstructured data, such as texts, audio, and videos, are still difficult to be embedded in the feat...
IEEE transactions on neural networks and learning systems
Apr 4, 2022
Recently, there has been a surge of interest in applying memristors to hardware implementations of deep neural networks due to various desirable properties of the memristor, such as nonvolativity, multivalue, and nanosize. Most existing neural networ...
IEEE transactions on neural networks and learning systems
Apr 4, 2022
Recent studies on semantic segmentation are exploiting contextual information to address the problem of inconsistent parsing prediction in big objects and ignorance in small objects. However, they utilize multilevel contextual information equally acr...
IEEE transactions on neural networks and learning systems
Apr 4, 2022
Recurrent neural networks (RNNs) can remember temporal contextual information over various time steps. The well-known gradient vanishing/explosion problem restricts the ability of RNNs to learn long-term dependencies. The gate mechanism is a well-dev...