AIMC Topic: Pattern Recognition, Automated

Clear Filters Showing 801 to 810 of 1689 articles

Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems
Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems. However, the successful application of these methods in motor imagery (MI) brain-compu...

A Novel Neural Network Model for Blood Pressure Estimation Using Photoplethesmography without Electrocardiogram.

Journal of healthcare engineering
The prevention, evaluation, and treatment of hypertension have attracted increasing attention in recent years. As photoplethysmography (PPG) technology has been widely applied to wearable sensors, the noninvasive estimation of blood pressure (BP) usi...

Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach.

Psychiatry research. Neuroimaging
In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to investigate whether the structural brain patterns in first episode psychosis (FEP) patients would be more similar to patients with chronic schizophrenia (SCZ) o...

Deep learning with convolutional neural network in radiology.

Japanese journal of radiology
Deep learning with a convolutional neural network (CNN) is gaining attention recently for its high performance in image recognition. Images themselves can be utilized in a learning process with this technique, and feature extraction in advance of the...

Multi-channel multi-scale fully convolutional network for 3D perivascular spaces segmentation in 7T MR images.

Medical image analysis
Accurate segmentation of perivascular spaces (PVSs) is an important step for quantitative study of PVS morphology. However, since PVSs are the thin tubular structures with relatively low contrast and also the number of PVSs is often large, it is chal...

Predication of different stages of Alzheimer's disease using neighborhood component analysis and ensemble decision tree.

Journal of neuroscience methods
BACKGROUND: There is a spectrum of the progression from healthy control (HC) to mild cognitive impairment (MCI) without conversion to Alzheimer's disease (AD), to MCI with conversion to AD (cMCI), and to AD. This study aims to predict the different d...

An adaptive deep Q-learning strategy for handwritten digit recognition.

Neural networks : the official journal of the International Neural Network Society
Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further im...

Biologically Inspired Intensity and Depth Image Edge Extraction.

IEEE transactions on neural networks and learning systems
In recent years, artificial vision research has moved from focusing on the use of only intensity images to include using depth images, or RGB-D combinations due to the recent development of low-cost depth cameras. However, depth images require a lot ...

Computer Aided Solution for Automatic Segmenting and Measurements of Blood Leucocytes Using Static Microscope Images.

Journal of medical systems
Blood leucocytes segmentation in medical images is viewed as difficult process due to the variability of blood cells concerning their shape and size and the difficulty towards determining location of Blood Leucocytes. Physical analysis of blood tests...

Robust Latent Regression with discriminative regularization by leveraging auxiliary knowledge.

Neural networks : the official journal of the International Neural Network Society
For a domain adaptation learning problem, how to minimize the distribution mismatch between different domains is one of key challenges. In real applications, it is reasonable to obtain an optimal latent space for both domains so as to reduce the doma...