AIMC Topic: Pattern Recognition, Automated
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Fast Gaussian Naïve Bayes for searchlight classification analysis.
NeuroImage
Sep 4, 2017
The searchlight technique is a variant of multivariate pattern analysis (MVPA) that examines neural activity across large sets of small regions, exhaustively covering the whole brain. This usually involves application of classifier algorithms across ...
3-D Object Recognition of a Robotic Navigation Aid for the Visually Impaired.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 1, 2017
This paper presents a 3-D object recognition method and its implementation on a robotic navigation aid to allow real-time detection of indoor structural objects for the navigation of a blind person. The method segments a point cloud into numerous pla...
Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 1, 2017
Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the class...
Identification and segmentation of myelinated nerve fibers in a cross-sectional optical microscopic image using a deep learning model.
Journal of neuroscience methods
Aug 31, 2017
BACKGROUND: The morphometric analysis of myelinated nerve fibers of peripheral nerves in cross-sectional optical microscopic images is valuable. Several automated methods for nerve fiber identification and segmentation have been reported. This paper ...
Learning-based automated segmentation of the carotid artery vessel wall in dual-sequence MRI using subdivision surface fitting.
Medical physics
Aug 30, 2017
PURPOSE: The quantification of vessel wall morphology and plaque burden requires vessel segmentation, which is generally performed by manual delineations. The purpose of our work is to develop and evaluate a new 3D model-based approach for carotid ar...
LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks.
IEEE transactions on visualization and computer graphics
Aug 29, 2017
Recurrent neural networks, and in particular long short-term memory (LSTM) networks, are a remarkably effective tool for sequence modeling that learn a dense black-box hidden representation of their sequential input. Researchers interested in better ...
A Machine Learning Approach to Automated Gait Analysis for the Noldus Catwalk System.
IEEE transactions on bio-medical engineering
Aug 24, 2017
OBJECTIVE: Gait analysis of animal disease models can provide valuable insights into in vivo compound effects and thus help in preclinical drug development. The purpose of this paper is to establish a computational gait analysis approach for the Nold...
Effects of spatial fMRI resolution on the classification of naturalistic movies.
NeuroImage
Aug 24, 2017
Studies involving multivariate pattern analysis (MVPA) of BOLD fMRI data generally attribute the success of the information-theoretic approach to BOLD signal contrast on the fine spatial scale of millimeters facilitating the classification or decodin...
Discriminatively Trained Latent Ordinal Model for Video Classification.
IEEE transactions on pattern analysis and machine intelligence
Aug 22, 2017
We address the problem of video classification for facial analysis and human action recognition. We propose a novel weakly supervised learning method that models the video as a sequence of automatically mined, discriminative sub-events (e.g., onset a...
Discovering associations between adverse drug events using pattern structures and ontologies.
Journal of biomedical semantics
Aug 22, 2017
BACKGROUND: Patient data, such as electronic health records or adverse event reporting systems, constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequently associated ADEs in subgro...
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