AIMC Topic: Databases, Factual

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Multi-view projected clustering with graph learning.

Neural networks : the official journal of the International Neural Network Society
Graph based multi-view learning is well known due to its effectiveness and good clustering performance. However, most existing methods directly construct graph from original high-dimensional data which always contain redundancy, noise and outlying en...

Chronic gastritis classification using gastric X-ray images with a semi-supervised learning method based on tri-training.

Medical & biological engineering & computing
High-quality annotations for medical images are always costly and scarce. Many applications of deep learning in the field of medical image analysis face the problem of insufficient annotated data. In this paper, we present a semi-supervised learning ...

A Smartphone Lightweight Method for Human Activity Recognition Based on Information Theory.

Sensors (Basel, Switzerland)
Smartphones have emerged as a revolutionary technology for monitoring everyday life, and they have played an important role in Human Activity Recognition (HAR) due to its ubiquity. The sensors embedded in these devices allows recognizing human behavi...

Multi-way backpropagation for training compact deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Depth is one of the key factors behind the success of convolutional neural networks (CNNs). Since ResNet (He et al., 2016), we are able to train very deep CNNs as the gradient vanishing issue has been largely addressed by the introduction of skip con...

Data science and machine learning in anesthesiology.

Korean journal of anesthesiology
Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods that are largely inference-based, ML is geared more towards making accurate predictions. ML is a field of artificial intelligence concerned with devel...

Automatic discovery of resource-restricted Convolutional Neural Network topologies for myoelectric pattern recognition.

Computers in biology and medicine
Convolutional Neural Networks (CNNs) have been subject to extensive attention in the pattern recognition literature due to unprecedented performance in tasks of information extraction from unstructured data. Whereas available methods for supervised t...

Deep learning based searching approach for RDF graphs.

PloS one
The Internet is a remarkably complex technical system. Its rapid growth has also brought technical issues such as problems to information retrieval. Search engines retrieve requested information based on the provided keywords. Consequently, it is dif...

Predicting Optimal Hypertension Treatment Pathways Using Recurrent Neural Networks.

International journal of medical informatics
BACKGROUND: In ambulatory care settings, physicians largely rely on clinical guidelines and guideline-based clinical decision support (CDS) systems to make decisions on hypertension treatment. However, current clinical evidence, which is the knowledg...

Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics.

Neural networks : the official journal of the International Neural Network Society
We examine the efficiency of Recurrent Neural Networks in forecasting the spatiotemporal dynamics of high dimensional and reduced order complex systems using Reservoir Computing (RC) and Backpropagation through time (BPTT) for gated network architect...