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Chapter and Conference Paper
Speech Segregation Using Constrained ICA
In natural environment, speech often occurs concurrently with acoustic interference. How to effectively extract speech remains a great challenge. This paper describes a novel constrained Independent Component ...
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Chapter and Conference Paper
A Fast Decryption Algorithm for BSS-Based Image Encryption
The image encryption based on blind source separation (BSS) takes advantage of the underdetermined BSS problem to encrypt multiple confidential images. Its security can be further improved if the number of ima...
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Chapter and Conference Paper
A Semi-blind Complex ICA Algorithm for Extracting a Desired Signal Based on Kurtosis Maximization
Semi-blind independent component analysis (ICA) incorporates some prior information into standard blind ICA, and thus solves some problems of blind ICA as well as provides improved performance. However, semi-b...
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Chapter and Conference Paper
Constrained Complex-Valued ICA without Permutation Ambiguity Based on Negentropy Maximization
Complex independent component analysis (ICA) has found utility in separation of complex-valued signals such as communications, functional magnetic resonance imaging, and frequency-domain speeches. However, per...
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Chapter and Conference Paper
Speech Separation via Parallel Factor Analysis of Cross-Frequency Covariance Tensor
This paper considers separation of convolutive speech mixtures in frequency-domain within a tensorial framework. By assuming that components associated with neighboring frequency bins of the same source are st...
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Chapter and Conference Paper
A Novel F-Pad for Handwriting Force Information Acquisition
This paper presents a novel pad for handwriting force information acquisition. The pad named F-Pad (force-pad) is capable of capturing both the dynamic handwriting information and the static trajectory of the ...
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Chapter and Conference Paper
Complex Non-Orthogonal Joint Diagonalization Based on LU and LQ Decompositions
In this paper, we propose a class of complex non-orthogonal joint diagonalization (NOJD) algorithms with successive rotations. The proposed methods consider LU or LQ decompositions of the mixing matrices, and ...
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Chapter and Conference Paper
Clustering of MRI Radiomics Features for Glioblastoma Multiforme: An Initial Study
This paper proposed a radiomics model from magnetic resonance imaging (MRI) for Glioblastoma Multiforme (GBM) patients. One challenge of radiomics study is to reduce the redundancy of the features. Totally 466...
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Chapter and Conference Paper
Comparison of Functional Network Connectivity and Granger Causality for Resting State fMRI Data
Functional network connectivity (FNC) and Granger causality have been widely used to identify functional and effective connectivity for resting functional magnetic resonance imaging (fMRI) data. However, the r...
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Chapter and Conference Paper
Rapid Triangle Matching Based on Binary Descriptors
Geometric constraints have been widely applied to image matching to gain additional advantages over feature points. A rapid triangle matching (RTM) algorithm was such an algorithm for matching triangles formed...
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Chapter and Conference Paper
Comparison of Two Swarm Intelligence Algorithms: From the Viewpoint of Learning
It is always said that learning is at the core of intelligence. How does learning work in swarm intelligence algorithms (SIAs)? This paper tries to answer this question by analyzing the learning mechanisms in ...
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Chapter and Conference Paper
Fusion of Laser Point Clouds and Color Images with Post-calibration
Fusion of laser point clouds and color images has a great advantage in the photogrammetry, computer vision, and computer graphics communities. Most of existing methods estimate the projection matrix for mappin...
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Chapter and Conference Paper
Image Edge Detection for Stitching Aerial Images with Geometrical Rectification
Changes of the flight attitude of unmanned aircraft cause nonlinear distortion in the aerial images. Stitching these images without geometric rectification may cause the problem of mismatching. However, the ge...
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Chapter and Conference Paper
Emotion Recognition Based on Gramian Encoding Visualization
This paper addresses the problem that emotional computing is difficult to be put into real practical fields intuitively, such as medical disease diagnosis and so on, due to poor direct understanding of physiol...
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Chapter and Conference Paper
Multi-view Emotion Recognition Using Deep Canonical Correlation Analysis
Emotion is a subjective, conscious experience when people face different kinds of stimuli. In this paper, we adopt Deep Canonical Correlation Analysis (DCCA) for high-level coordinated representation to make f...
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Chapter and Conference Paper
A Secure Color-Code Key Exchange Protocol for Mobile Chat Application
This paper proposes a secure color-code key exchange protocol for secure mobile chat applications (MC APPs). This proposed protocol in this paper is a novel approach which the exchanged color-code coding sessi...
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Chapter and Conference Paper
Classification of Schizophrenia Patients and Healthy Controls Using ICA of Complex-Valued fMRI Data and Convolutional Neural Networks
Deep learning has contributed greatly to functional magnetic resonance imaging (fMRI) analysis, however, spatial maps derived from fMRI data by independent component analysis (ICA), as promising biomarkers, ha...
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Chapter and Conference Paper
A Deep Learning Approach to Detecting Changes in Buildings from Aerial Images
Detecting building changes via aerial images acquired at different times is important in the urban planning and geographic information updating. Deep learning solutions have high potential in improving detecti...
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Chapter and Conference Paper
Canonical Polyadic Decomposition with Constant Modulus Constraint: Application to Polarization Sensitive Array Processing
We consider the joint estimation of direction-of-arrival (DOA) and polarization of constant modulus (CM) signals based on a polarization sensitive array. We propose an algebraic algorithm for canonical polyadi...
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Chapter and Conference Paper
Marginal Spectrum Modulated Hilbert-Huang Transform: Application to Time Courses Extracted by Independent Vector Analysis of Resting-State fMRI Data
Hilbert-Huang transform (HHT) can reveal abnormal activations impacted by mental disorders from regions of interest (ROIs) based functional magnetic resonance imaging (fMRI) data with high temporal and frequen...