AIMC Topic: Neural Networks, Computer

Clear Filters Showing 22921 to 22930 of 31376 articles

Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram.

Physiological measurement
OBJECTIVE: This study classifies sleep stages from a single lead electrocardiogram (ECG) using beat detection, cardiorespiratory coupling in the time-frequency domain and a deep convolutional neural network (CNN).

Analysis of intensity normalization for optimal segmentation performance of a fully convolutional neural network.

Zeitschrift fur medizinische Physik
INTRODUCTION: Convolutional neural networks have begun to surpass classical statistical- and atlas based machine learning techniques in medical image segmentation in recent years, proving to be superior in performance and speed. However, a major chal...

Automated beat-wise arrhythmia diagnosis using modified U-net on extended electrocardiographic recordings with heterogeneous arrhythmia types.

Computers in biology and medicine
Abnormality of the cardiac conduction system can induce arrhythmia - abnormal heart rhythm - that can frequently lead to other cardiac diseases and complications, and are sometimes life-threatening. These conduction system perturbations can manifest ...

Automated diagnosis of breast ultrasonography images using deep neural networks.

Medical image analysis
Ultrasonography images of breast mass aid in the detection and diagnosis of breast cancer. Manually analyzing ultrasonography images is time-consuming, exhausting and subjective. Automated analyzing such images is desired. In this study, we develop a...

Fast animal pose estimation using deep neural networks.

Nature methods
The need for automated and efficient systems for tracking full animal pose has increased with the complexity of behavioral data and analyses. Here we introduce LEAP (LEAP estimates animal pose), a deep-learning-based method for predicting the positio...

'Artiphysiology' reveals V4-like shape tuning in a deep network trained for image classification.

eLife
Deep networks provide a potentially rich interconnection between neuroscientific and artificial approaches to understanding visual intelligence, but the relationship between artificial and neural representations of complex visual form has not been el...

PENYEK: Automated brown planthopper detection from imperfect sticky pad images using deep convolutional neural network.

PloS one
Rice is a staple food in Asia and it contributes significantly to the Gross Domestic Product (GDP) of Malaysia and other developing countries. Brown Planthopper (BPH) causes high levels of economic loss in Malaysia. Identification of BPH presence and...

Deep Learning in Image Cytometry: A Review.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and how it is ap...

Research on a learning rate with energy index in deep learning.

Neural networks : the official journal of the International Neural Network Society
The stochastic gradient descent algorithm (SGD) is the main optimization solution in deep learning. The performance of SGD depends critically on how learning rates are tuned over time. In this paper, we propose a novel energy index based optimization...

Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network.

Medical image analysis
Synthesized medical images have several important applications. For instance, they can be used as an intermedium in cross-modality image registration or used as augmented training samples to boost the generalization capability of a classifier. In thi...