85,824 results match your criteria IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council[Journal]


IoT-Based Services and Applications for Mental Health in the Literature.

J Med Syst 2018 Dec 6;43(1):11. Epub 2018 Dec 6.

Psiquiatry Service, Hospital Zamora, Hernán Cortés, Zamora, Spain.

Internet of Things (IoT) has emerged as a new paradigm today, connecting a variety of physical and virtual elements integrated with electronic components, sensors, actuators and software to collect and exchange data. IoT is gaining increasing attention as a priority research topic in the Health sector in general and in specific areas such as Mental Health. The main objective of this paper is to show a review of the existing research works in the literature, referring to the main IoT services and applications in Mental Health diseases. Read More

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December 2018
2 Reads

Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection.

Eur Radiol 2018 Dec 5. Epub 2018 Dec 5.

CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

Objectives: The present study aimed to investigate the clinical prognostic significance of radiomics signature (R-signature) in patients with gastric cancer who had undergone radical resection.

Methods: A total of 181 patients with gastric cancer who had undergone radical resection were enrolled in this retrospective study. The association between the R-signature and overall survival (OS) was assessed in the primary cohort and verified in the validation cohort. Read More

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December 2018

Closed-Loop Intravenous Drug Administration Using Photoplethysmography.

IEEE J Transl Eng Health Med 2018 1;6:4300108. Epub 2018 Nov 1.

Department of Biomedical EngineeringUniversity of UtahSalt Lake CityUT84112USA.

An optically-based injection control system has been developed for preclinical use for an intravenous drug delivery application. Current clinical drug delivery for oncology typically provides for intravenous administration without an awareness of achieved plasma concentration, yet interpatient variability produces consequences ranging from toxicity to ineffectual treatments. We report a closed-loop injection system integrating a pulse-photoplethysmograph to measure the concentration of an injected agent in the circulating blood system using a previously described technique. Read More

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November 2018

Stroke Patients' Acceptance of a Smart Garment for Supporting Upper Extremity Rehabilitation.

IEEE J Transl Eng Health Med 2018 18;6:2101009. Epub 2018 Oct 18.

Industrial Design DepartmentEindhoven University of Technology5612AZEindhovenThe Netherlands.

The objective is to evaluate to which extent that a garment equipped with sensors that can support posture monitoring can be used in upper extremity rehabilitation training of stroke patients. Seventeen stroke survivors (mean age: 55 years old, SD =13.5) were recruited in three hospitals in Shanghai. Read More

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October 2018

Superbubbles revisited.

Algorithms Mol Biol 2018 1;13:16. Epub 2018 Dec 1.

1Competence Center for Scalable Data Services and Solutions Dresden/Leipzig, Universität Leipzig, Augustusplatz 12, 04107 Leipzig, Germany.

Background: Superbubbles are distinctive subgraphs in direct graphs that play an important role in assembly algorithms for high-throughput sequencing (HTS) data. Their practical importance derives from the fact they are connected to their host graph by a single entrance and a single exit vertex, thus allowing them to be handled independently. Efficient algorithms for the enumeration of superbubbles are therefore of important for the processing of HTS data. Read More

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December 2018

Scalable Large-Margin Distance Metric Learning Using Stochastic Gradient Descent.

IEEE Trans Cybern 2018 Nov 29. Epub 2018 Nov 29.

The key to success of many machine learning and pattern recognition algorithms is the way of computing distances between the input data. In this paper, we propose a large-margin-based approach, called the large-margin distance metric learning (LMDML), for learning a Mahalanobis distance metric. LMDML employs the principle of margin maximization to learn the distance metric with the goal of improving k-nearest-neighbor classification. Read More

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November 2018

Event-Triggered Recursive Filtering for Shift-Varying Linear Repetitive Processes.

IEEE Trans Cybern 2018 Dec 3. Epub 2018 Dec 3.

This paper addresses the recursive filtering problem for shift-varying linear repetitive processes (LRPs) with limited network resources. To reduce the resource occupancy, a novel event-triggered strategy is proposed where the concern is to broadcast those necessary measurements to update the innovation information only when certain events appear. The primary goal of this paper is to design a recursive filter rendering that, under the event-triggered communication mechanism, an upper bound (UB) on the filtering error variance is ensured and then optimized by properly determining the filter gains. Read More

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December 2018

PPLS/D: Parallel Pareto Local Search Based on Decomposition.

IEEE Trans Cybern 2018 Nov 29. Epub 2018 Nov 29.

Pareto local search (PLS) is a basic building block in many metaheuristics for a multiobjective combinatorial optimization problem. In this paper, an enhanced PLS variant called parallel PLS based on decomposition (PPLS/D) is proposed. PPLS/D improves the efficiency of PLS using the techniques of parallel computation and problem decomposition. Read More

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November 2018

Output-Based Dynamic Event-Triggered Mechanisms for Disturbance Rejection Control of Networked Nonlinear Systems.

IEEE Trans Cybern 2018 Dec 3. Epub 2018 Dec 3.

This paper proposes a new output-based dynamic event-triggered mechanism (ETM) for disturbance rejection control of a class of networked nonlinear uncertain systems subject to additive time-varying disturbance. In the proposed control method, a new robust output feedback controller is first designed based on a generalized proportional-integral observer to attenuate/compensate the undesirable influence of nonlinear uncertainties and disturbances. Different from the static ETM, two new dynamic variables are defined, and thereafter, two kinds of different discrete-time dynamic ETMs are developed only using the sampled-data output signal, such that a better tradeoff between the communication properties and the control properties can be obtained. Read More

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December 2018

Automatic Graph-based Modeling of Brain Microvessels Captured with Two-Photon Microscopy.

IEEE J Biomed Health Inform 2018 Dec 3. Epub 2018 Dec 3.

Graph models of cerebral vasculature derived from 2-photon microscopy have shown to be relevant to study brain microphysiology. Automatic graphing of these microvessels remain problematic due to the vascular network complexity and 2-photon sensitivity limitations with depth. In this work, we propose a fully automatic processing pipeline to address this issue. Read More

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December 2018
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Unconstrained Estimation of HRV Indices after Removing Respiratory Influences from Heart Rate.

IEEE J Biomed Health Inform 2018 Dec 3. Epub 2018 Dec 3.

Objective: This paper proposes an approach to better estimate the sympathovagal balance (SB) and the respiratory sinus arrhythmia (RSA) after separating respiratory influences from the heart rate (HR).

Methods: The separation is performed using orthogonal subspace projections and the approach is first tested using simulated HR and respiratory signals with different spectral properties. Then, RSA and SB are estimated during autonomic blockade and stress using the proposed approach and the classical heart rate variability (HRV) analysis. Read More

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December 2018

Intuitionistic Center-Free FCM Clustering for MR Brain Image Segmentation.

IEEE J Biomed Health Inform 2018 Nov 30. Epub 2018 Nov 30.

In this paper, an intuitionistic center-free fuzzy c-means clustering method (ICFFCM) is proposed for magnetic resonance (MR) brain image segmentation. Firstly, in order to suppress the effect of noise in MR brain images, a pixel-to-pixel similarity with spatial information is defined. Then, for the purpose of handling the vagueness in MR brain images as well as the uncertainty in clustering process, a pixel-to-cluster similarity measure is defined by employing the intuitionistic fuzzy membership function. Read More

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November 2018

A Novel and Safe Two-Stage Screening Method for Support Vector Machine.

IEEE Trans Neural Netw Learn Syst 2018 Dec 3. Epub 2018 Dec 3.

To make support vector machine (SVM) applicable to large-scale data sets, safe screening rules are developed recently. The main idea is to reduce the scale of SVM by safely discarding the redundant training samples. Among existing safe screening rules, the dual screening method with variational inequalities (DVI) and the dynamic screening rule (DSR) based on duality gap are two representative strategies. Read More

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December 2018

imPhy: Imputing Phylogenetic Trees with Missing Information using Mathematical Programming.

IEEE/ACM Trans Comput Biol Bioinform 2018 Nov 30. Epub 2018 Nov 30.

Given a set of organisms, the available corresponding genetic information is often incomplete and most gene trees fail to contain all individuals. This incompleteness causes difficulties in data collection, information extraction, and gene tree inference. Outlying gene trees may represent horizontal gene transfers, gene duplications, hybridizations, but they are difficult to detect in the presence of missing data. Read More

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November 2018

Development and evaluation of multistructured and hierarchical epidermal growth factor-poly (ε-caprolactone) scaffolds.

IEEE Trans Nanobioscience 2018 Nov 30. Epub 2018 Nov 30.

In this study, we separately fabricated the poly (ε-caprolactone) (PCL) scaffolds containing epidermal growth factor (EGF) by using our-self fabricated electrospinning machine for tissue regeneration application. Several fundamental properties, including the dimensions, wettability and EGF release profiles, of the fabricated EGF-PCL the bead, fibrous and multistructured scaffolds were characterised by using the Scanning Electron Microscopy (SEM), contact angle goniometer and vertical diffusion system. The EGF release profiles of three scaffolds were measured for 200 hours and the multistructured scaffold performed stable and long EGF release properties. Read More

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November 2018
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Learning Spatial-Spectral-Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment.

IEEE Trans Neural Syst Rehabil Eng 2018 Dec 3. Epub 2018 Dec 3.

Mental workload assessment is essential for maintaining human health and preventing accidents. Most research on this issue is limited to a single task. However, cross-task assessment is indispensable for extending a pre-trained model to new workload conditions. Read More

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December 2018

Scene Transitions and Teleportation in Virtual Reality and the Implications for Spatial Awareness and Sickness.

IEEE Trans Vis Comput Graph 2018 Nov 30. Epub 2018 Nov 30.

Various viewing and travel techniques are used in immersive virtual reality to allow users to see different areas or perspectives of 3D environments. Our research evaluates techniques for visually showing transitions between two viewpoints in head-tracked virtual reality. We present four experiments that focus on automated viewpoint changes that are controlled by the system rather than by interactive user control. Read More

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November 2018

Simulating Liquids on Dynamically Warping Grids.

IEEE Trans Vis Comput Graph 2018 Nov 30. Epub 2018 Nov 30.

We introduce dynamically warping grids for adaptive liquid simulation. Our primary contributions are a strategy for dynamically deforming regular grids over the course of a simulation and a method for efficiently utilizing these deforming grids for liquid simulation. Prior work has shown that unstructured grids are very effective for adaptive fluid simulations. Read More

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November 2018

Deep Online Video Stabilization with Multi-Grid Warping Transformation Learning.

IEEE Trans Image Process 2018 Nov 30. Epub 2018 Nov 30.

Video stabilization techniques are essential for most hand-held captured videos due to high-frequency shakes. Several 2D, 2.5D and 3D-based stabilization techniques have been presented previously, but to our knowledge, no solutions based on deep neural networks had been proposed to date. Read More

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November 2018

A Perceptual Distinguishability Predictor For JND-noise-contaminated Images.

IEEE Trans Image Process 2018 Dec 3. Epub 2018 Dec 3.

Just noticeable difference (JND) models are widely used for perceptual redundancy estimation in images and videos. A common method for measuring the accuracy of a JND model is to inject random noise in an image based on the JND model, and check whether the JND-noise-contaminated image is perceptually distinguishable from the original image or not. Also, when comparing the accuracy of two different JND models, the model that produces the JND-noise-contaminated image with better quality at the same level of noise energy is the better model. Read More

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December 2018

Low-resolution Face Recognition in the Wild via Selective Knowledge Distillation.

IEEE Trans Image Process 2018 Nov 30. Epub 2018 Nov 30.

Typically, the deployment of face recognition models in the wild needs to identify low-resolution faces with extremely low computational cost. To address this problem, a feasible solution is compressing a complex face model to achieve higher speed and lower memory at the cost of minimal performance drop. Inspired by that, this paper proposes a learning approach to recognize low-resolution faces via selective knowledge distillation. Read More

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November 2018

Evaluation of Reconstruction Parameters for Two-Dimensional Comb-push Ultrasound Shear Wave Elastography.

IEEE Trans Ultrason Ferroelectr Freq Control 2018 Nov 30. Epub 2018 Nov 30.

Shear wave elastography (SWE) is a noninvasive ultrasound imaging modality used in the assessment of the mechanical properties of tissues such as the liver, kidney, skeletal muscle, thyroid and the breast. Among the methods used to perform SWE is the comb-push ultrasound shear elastography (CUSE) method. This method uses multiple focused ultrasound beams to generate push beams with acoustic radiation force. Read More

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November 2018

Surface Area Enhancement of Nanomechanical Disk Resonators Using MWCNT for Mass Sensing Applications.

IEEE Trans Ultrason Ferroelectr Freq Control 2018 Nov 30. Epub 2018 Nov 30.

This work presents fabrication of thermal-piezoresistive nanoelectromechanical (NEM) silicon disk resonators and their characterization as highly sensitive mass sensors. Forest of multiwall carbon nanotubes (MWCNT) has been grown on top surface of the fabricated devices increasing the resonator effective surface area, which in turn increases the adsorption capacity and therefore frequency shift of the sensor in molecular or particulate detection applications. To investigate the effect of the enhanced surface area on frequency shift, devices with and without MWCNTs were exposed to an aqueous solution of manganese sulfate for different deposition times and the resonance frequency shift was recorded accordingly. Read More

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November 2018
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Conductivity Tensor Imaging of In Vivo Human Brain and Experimental Validation using Giant Vesicle Suspension.

IEEE Trans Med Imaging 2018 Dec 3. Epub 2018 Dec 3.

Human brain mapping of low-frequency electrical conductivity tensors can realize patient-specific volume conductor models for neuroimaging and electrical stimulation. We report experimental validation and in vivo human experiments of a new electrodeless conductivity tensor imaging (CTI) method. From CTI imaging of a giant vesicle suspension using a 9. Read More

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December 2018

3D auto-context-based locality adaptive multi-modality GANs for PET synthesis.

IEEE Trans Med Imaging 2018 Nov 29. Epub 2018 Nov 29.

Positron emission tomography (PET) has been substantially used recently. To minimize the potential health risk caused by the tracer radiation inherent to PET scans, it is of great interest to synthesize the high-quality PET image from the low-dose one to reduce the radiation exposure. In this paper, we propose a 3D auto-context-based locality adaptive multi-modality generative adversarial networks model (LA-GANs) to synthesize the high-quality FDG PET image from the low-dose one with the accompanying MRI images that provide anatomical information. Read More

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November 2018

Incremental Learning Through Deep Adaptation.

IEEE Trans Pattern Anal Mach Intell 2018 Nov 30. Epub 2018 Nov 30.

Given an existing trained neural network, it is often desirable to learn new capabilities without hindering performance of those already learned. Existing approaches either learn sub-optimal solutions, require joint training, or incur a substantial increment in the number of parameters for each added domain, typically as many as the original network. We propose a method called Deep Adaptation Modules (DAM) that constrains newly learned filters to be linear combinations of existing ones. Read More

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November 2018

A comprehensive database for benchmarking imaging systems.

IEEE Trans Pattern Anal Mach Intell 2018 Nov 30. Epub 2018 Nov 30.

Cross-modality face recognition is an emerging topic due to the wide-spread usage of different sensors in day-to-day life applications. The development of face recognition systems relies greatly on existing databases for evaluation and obtaining training examples for data-hungry machine learning algorithms. However, currently, there is no publicly available face database that includes more than two modalities for the same subject. Read More

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November 2018
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Image-Aligned Dynamic Liver Reconstruction Using Intra-Operative Field of Views for Minimal Invasive Surgery.

IEEE Trans Biomed Eng 2018 Nov 30. Epub 2018 Nov 30.

During hepatic minimal invasive surgery (MIS), 3D reconstruction of a liver surface by interpreting the geometry of its soft-tissues is achieving attractions. One of the major issues to be addressed in MIS is liver deformation. Moreover, it severely inhibits free sight and dexterity of tissue manipulation which causes its intra-operative morphology and soft tissue motion altered as compared to its pre-operative shape. Read More

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November 2018
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Improvement in Recovery of Hemodynamic Responses by Extended Kalman Filter with Non-Linear State-Space Model and Short Separation Measurement.

IEEE Trans Biomed Eng 2018 Nov 30. Epub 2018 Nov 30.

Objective: The purpose of this study is to describe the noise reduction in the hemodynamic responses, obtained by functional near-infrared spectroscopy (fNIRS), using the proposed extended Kalman filter (EKF) with a non-linear state-space model, aided by the short separation (SS) measurement.

Methods: The authors used the simulated data by adding the synthetic hemodynamic response function (HRF) to the multi-distance four-channel fNIRS signals obtained during the resting state. EKF was used to estimate the non-linear state-space model designed based on Balloon model. Read More

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November 2018

Prior Knowledge-Based Probabilistic Collaborative Representation for Visual Recognition.

IEEE Trans Cybern 2018 Nov 26. Epub 2018 Nov 26.

Collaborative representation is an effective way to design classifiers for many practical applications. In this paper, we propose a novel classifier, called the prior knowledge-based probabilistic collaborative representation-based classifier (PKPCRC), for visual recognition. Compared with existing classifiers which use the collaborative representation strategy, the proposed PKPCRC further includes characteristics of training samples of each class as prior knowledge. Read More

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November 2018

Edge-Based Fractional-Order Adaptive Strategies for Synchronization of Fractional-Order Coupled Networks With Reaction-Diffusion Terms.

IEEE Trans Cybern 2018 Nov 28. Epub 2018 Nov 28.

In this paper, spatial diffusions are introduced to fractional-order coupled networks and the problem of synchronization is investigated for fractional-order coupled neural networks with reaction-diffusion terms. First, a new fractional-order inequality is established based on the Caputo partial fractional derivative. To realize asymptotical synchronization, two types of adaptive coupling weights are considered, namely: 1) coupling weights only related to time and 2) coupling weights dependent on both time and space. Read More

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November 2018

Embedding Attention and Residual Network for Accurate Salient Object Detection.

IEEE Trans Cybern 2018 Nov 27. Epub 2018 Nov 27.

Salient object detection is usually used as a preprocessing step to facilitate a variety of subsequent applications which should take little time cost. With the quick development of deep learning recently, profound progresses have been made to achieve a new state-of-the-art performance. However, the learned features of the existing deep learning-based methods are not accurate enough thus leading to unsatisfactory detection in complex scenes, such as low contrast or very similar between salient object and background region and multiple (small) salient objects with diverse characteristics. Read More

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November 2018

Risk Prediction Model for Late Life Depression: Development and Validation on Three Large European Datasets.

IEEE J Biomed Health Inform 2018 Nov 29. Epub 2018 Nov 29.

Assessing the risk to develop a specific disease is the first step towards prevention, both at individual and population level. The development and validation of Risk Prediction Models (RPMs) is the norm within different fields of medicine but still underused in psychiatry, despite the global impact of mental disorders. In particular, there is a lack of RPMs to assess the risk of developing depression, the first worldwide cause of disability and harbinger of functional decline in old age. Read More

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November 2018
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Identification of Drug-side Effect Association via Semi-supervised Model and Multiple Kernel Learning.

IEEE J Biomed Health Inform 2018 Nov 28. Epub 2018 Nov 28.

Drug-side effect association contains the information on marketed medicines and their recorded adverse drug reactions. Traditional experimental method takes time consuming and expensive. All associations of drugs and side-effects are seen as a bipartite network. Read More

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November 2018
5 Reads

Into the Wild: The Challenges of Physiological Stress Detection in Laboratory and Ambulatory Settings.

IEEE J Biomed Health Inform 2018 Nov 28. Epub 2018 Nov 28.

Stress and mental health have become major concerns worldwide. Research has already extensively investigated physiological signals as quantitative and continuous markers of stress. In recent years the focus of the field has shifted from the laboratory to the ambulatory environment. Read More

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November 2018

Effects of State-Dependent Impulses on Robust Exponential Stability of Quaternion-Valued Neural Networks Under Parametric Uncertainty.

IEEE Trans Neural Netw Learn Syst 2018 Nov 27. Epub 2018 Nov 27.

This paper addresses the state-dependent impulsive effects on robust exponential stability of quaternion-valued neural networks (QVNNs) with parametric uncertainties. In view of the noncommutativity of quaternion multiplication, we have to separate the concerned quaternion-valued models into four real-valued parts. Then, several assumptions ensuring every solution of the separated state-dependent impulsive neural networks intersects each of the discontinuous surface exactly once are proposed. Read More

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November 2018

Data Subset Selection With Imperfect Multiple Labels.

IEEE Trans Neural Netw Learn Syst 2018 Nov 27. Epub 2018 Nov 27.

We study the problem of selecting a subset of weakly labeled data where the labels of each data instance are redundant and imperfect. In real applications, less-than-expert labels are obtained at low cost in order to acquire many labels for each instance and then used for estimating the ground truth. However, on one side, preparing and processing data itself sometimes can be even more expensive than labeling. Read More

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November 2018
1 Read

The Complex Behaviour of a Simple Neural Oscillator Model in the Human Cortex.

IEEE Trans Neural Syst Rehabil Eng 2018 Nov 28. Epub 2018 Nov 28.

The brain is a complex organ responsible for memory storage and reasoning; however, the mechanisms underlying these processes remain unknown. The paper forms a contribution to a lot of theoretical studies devoted to regular or chaotic oscillations of interconnected neurons assuming that the smallest information unit in the brain is not a neuron but, instead, a coupling of inhibitory and excitatory neurons forming a simple oscillator. Several coefficients of variation for peak intervals and correlation coefficients for peak interval histograms are evaluated and the sensitivity of such oscillator units is tested to changes in initial membrane potentials, interconnection signal delays and changes in synaptic weights based on known histologically verified neuron couplings. Read More

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November 2018
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Batch Mode Query by Committee for Motor Imagery-Based BCI.

IEEE Trans Neural Syst Rehabil Eng 2018 Nov 28. Epub 2018 Nov 28.

Although brain-computer interface (BCI) has potential application in the rehabilitation of neural disease and performance improvement of the human in the loop system, it is restricted in the laboratory environment. One of the hindrances behind this restriction is the requirement of a long training data collection session for the user prior to operation of the system at each time. Several approaches have been proposed including the reduction of training data maintaining the robust performance. Read More

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November 2018

Complex tensor factorisation with PARAFAC2 for the estimation of brain connectivity from the EEG.

IEEE Trans Neural Syst Rehabil Eng 2018 Nov 28. Epub 2018 Nov 28.

Objective: The coupling between neuronal populations and its magnitude have been shown to be informative for various clinical applications. One method to estimate functional brain connectivity is with electroencephalography (EEG) from which the cross-spectrum between different sensor locations is derived. We wish to test the efficacy of tensor factorisation in the estimation of brain connectivity. Read More

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November 2018
4 Reads

Feature Tracking by Two-Step Optimization.

IEEE Trans Vis Comput Graph 2018 Nov 27. Epub 2018 Nov 27.

Tracking the temporal evolution of features in time-varying data is a key method in visualization. For typical feature definitions, such as vortices, objects are sparsely distributed over the data domain. In this paper, we present a novel approach for tracking both sparse and space-filling features. Read More

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November 2018

Spectral Image Fusion from Compressive Measurements.

IEEE Trans Image Process 2018 Nov 29. Epub 2018 Nov 29.

Compressive spectral imagers reduce the number of sampled pixels by coding and combining the spectral information. However, sampling compressed information with simultaneous high spatial and high spectral resolution demands expensive high-resolution sensors. This work introduces a model allowing data from high spatial/low spectral and low spatial/high spectral resolution compressive sensors to be fused. Read More

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November 2018

HyperReconNet: Joint Coded Aperture Optimization and Image Reconstruction for Compressive Hyperspectral Imaging.

IEEE Trans Image Process 2018 Nov 29. Epub 2018 Nov 29.

Coded aperture snapshot spectral imaging (CASSI) system encodes the 3D hyperspectral image (HSI) within a single 2D compressive image and then reconstructs the underlying HSI by employing an inverse optimization algorithm, which equips with the distinct advantage of snapshot but usually results in low reconstruction accuracy. To improve the accuracy, existing methods attempt to design either alternative coded apertures or advanced reconstruction methods, but cannot connect these two aspects via a unified framework, which limits the accuracy improvement. In this paper, we propose a convolution neural network (CNN) based endto- end method to boost the accuracy by jointly optimizing the coded aperture and the reconstruction method. Read More

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November 2018

Low Cost Edge Sensing for High Quality Demosaicking.

IEEE Trans Image Process 2018 Nov 28. Epub 2018 Nov 28.

Digital cameras that use Color Filter Arrays (CFA) entail a demosaicking procedure to form full RGB images. To digital camera industry, demosaicking speed is as important as demosaicking accuracy, because camera users have been accustomed to viewing captured photos instantly. Moreover, the cost associated with demosaicking should not go beyond the cost saved by using CFA. Read More

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November 2018
1 Read

Full-Vector Gradient for Multi-spectral or Multivariate Images.

IEEE Trans Image Process 2018 Nov 28. Epub 2018 Nov 28.

Gradient extraction is important for a lot of metrological applications such as Control Quality by Vision. In this work, we propose a full-vector gradient for multi-spectral sensors. The full-vector gradient extends Di Zenzo expression to take into account the non-orthogonality of the acquisition channels thanks to a Gram matrix. Read More

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November 2018

Two-Stream Convolutional Networks for Blind Image Quality Assessment.

IEEE Trans Image Process 2018 Nov 28. Epub 2018 Nov 28.

Traditional image quality assessment (IQA) methods cannot perform robustly, due to the shallow hand-designed features. It has been demonstrated that deep neural network can learn more effective features than ever. In this paper, we describe a new deep neural network to predict the image quality accurately without relying on the reference image. Read More

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November 2018
1 Read

Face Frontalization Using an Appearance-Flow-based Convolutional Neural Network.

IEEE Trans Image Process 2018 Nov 28. Epub 2018 Nov 28.

Facial pose variation is one of the major factors making face recognition (FR) a challenging task. One popular solution is to convert non-frontal faces to frontal ones on which face recognition is performed. Rotating faces causes facial pixel value changes. Read More

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November 2018
1 Read

Deep Ordinal Hashing with Spatial Attention.

IEEE Trans Image Process 2018 Nov 28. Epub 2018 Nov 28.

Hashing has attracted increasing research attention in recent years due to its high efficiency of computation and storage in image retrieval. Recent works have demonstrated the superiority of simultaneous feature representations and hash functions learning with deep neural networks. However, most existing deep hashing methods directly learn the hash functions by encoding the global semantic information, while ignoring the local spatial information of images. Read More

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November 2018

Parameter-Free Selective Segmentation with Convex Variational Methods.

IEEE Trans Image Process 2018 Nov 28. Epub 2018 Nov 28.

Selective segmentation methods involve incorporating user input to partition an image into a foreground and background. Often these methods are sensitive to some aspect of the user input in a counter intuitive manner, making their use in practice difficult. The most robust methods often involve laborious refinement on the part of the user, and sometimes editing/ supervision. Read More

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November 2018

Phase Noise and Frequency Stability of the Red-Pitaya Internal PLL.

IEEE Trans Ultrason Ferroelectr Freq Control 2018 Nov 28. Epub 2018 Nov 28.

In Field Programmable Gate Array platforms, the main clock is generally a low-cost quartz oscillator whose stability is of the order of 10-9 to 10-10 in the short term and 10-7 to 10-8 in the medium term, with uncertainty of tens of ppm. Better stability is achieved by feeding an external reference into the internal PLL. We report the noise characterization of the internal PLL of Red-Pitaya platform, an open-source embedded system architected around the Zynq 7010 System on Chip, with Analog to Digital and Digital to Analog Converters. Read More

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November 2018