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Article
A highly efficient ADMM-based algorithm for outlier-robust regression with Huber loss
Huber robust regression (HRR) has attracted much attention in machine learning due to its greater robustness to outliers compared to least-squares regression. However, existing algorithms for HRR are computati...
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Chapter and Conference Paper
Multimodal Wearable Device Signal Based Epilepsy Detection with Multi-scale Convolutional Neural Network
Seizure detection based on wearable devices has gradually become a popular research direction. The ability of wearable devices to capture signals is also improving, and a variety of physiological signals can b...
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Chapter and Conference Paper
Advanced License Plate Detector in Low-Quality Images with Smooth Regression Constraint
Improving the detection performance of license plate detectors in low-quality images is one of the core goals of license plate recognition community. While low-quality images encompasses various forms, this pa...
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Chapter and Conference Paper
Interictal EEG Based Prediction of ACTH Efficacy in Infantile Epileptic Spasms
Infantile epileptic spasms (IESS) are a common and refractory childhood epilepsy syndrome. Adrenocorticotropic hormone (ACTH) is one of the most effective drugs for the treatment of IESS disorder, but not effe...
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Article
Guest Editorial: machine learning for visual information processing & understanding
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Article
Recognizing knee pathologies by using gait dynamics via kernel principal component analysis and deterministic learning theory
This study concentrates on dynamical motion characteristics of knees during treadmill walking, and describes the application of kernel principal component analysis and deterministic learning theory to the dete...
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Article
Mean amplitude spectrum based epileptic state classification for seizure prediction using convolutional neural networks
An increasing number of algorithms have been proposed for epileptic seizure prediction in recent years. But most of them are based on a partition of the electroencephalograph (EEG) signal of an epileptic patie...
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Article
Multichannel Matrix Randomized Autoencoder
The existing randomized autoencoders are generally designed for vectorization data resulting in destroying the original structure information inevitably when dealing with multi-dimension data such as image and...
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Chapter and Conference Paper
Coherence Matrix Based Early Infantile Epileptic Encephalopathy Analysis with ResNet
EIEE syndrome, known as early infantile epileptic encephalopathy, is considered to be the earliest onset form of age-dependent epileptic encephalopathy. The main manifestations are tonic-spasmodic seizures in ...
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Chapter and Conference Paper
Incremental Quaternion Random Neural Networks
Quaternion, as a hypercomplex number with three imaginary elements, is effective in characterizing three- and four-dimensional vector signals. Quaternion neural networks with randomly generated quaternions as ...
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Chapter and Conference Paper
Transfer Learning Based Seizure Detection: A Review
Seizure detection automatically recognizes Electroencephalogram (EEG) signals in epileptic seizure states through machine learning, time-frequency analysis, statistical test, etc., which provides an objective ...
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Article
Early seizure detection in childhood focal epilepsy with electroencephalogram feature fusion on deep autoencoder learning and channel correlations
Recognition of epileptic electroencephalogram (EEG) signals is vital to epileptic seizure detection. Current research on seizure detection mostly focused on generalized seizure analysis. Compared with generali...
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Chapter and Conference Paper
Multi-modal Signal Based Childhood Rolandic Epilepsy Detection
Electroencephalogram (EEG) is the common signal used in epilepsy analysis but suffered from the inconvenient issue in data acquisition, especially when applied to children with Rolandic epilepsy. In this paper...
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Article
Joint Pyramid Feature Representation Network for Vehicle Re-identification
Vehicle re-identification (Re-ID) technology plays an important role in the intelligent transportation system for smart city. Due to various uncertain factors in the real-world scenarios, (e.g., resolution var...
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Chapter and Conference Paper
Weakly-Supervised Lesion-Aware and Consistency Regularization for Retinitis Pigmentosa Detection from Ultra-Widefield Images
Retinitis pigmentosa (RP) is one of the most common retinal diseases caused by gene defects, which can lead to night blindness or complete blindness. Accurate diagnosis and lesion identification are significan...
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Chapter and Conference Paper
Multi-scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection
Early mild cognitive impairment (EMCI) is an early stage of MCI, which can be detected by brain connectivity networks. To detect EMCI, we design a novel framework based on multi-scale enhanced GCN (MSE-GCN) in...
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Chapter and Conference Paper
Integrating Similarity Awareness and Adaptive Calibration in Graph Convolution Network to Predict Disease
Significant memory concern (SMC) is the earlier stage of mild cognitive impairment (MCI), and its early treatment is quite vital to delay further disease-induced deterioration. To predict the deterioration, gr...
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Article
Urban noise recognition with convolutional neural network
Urban noise recognition play a vital role in city management and safety operation, especially in the recent smart city engineering. Exiting studies on urban noise recognition are mostly based on conventional a...
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Article
Radar emitter identification with bispectrum and hierarchical extreme learning machine
Radar Emitter Identification (REI) has been broadly used in military and civil fields. In this paper, a novel method is proposed for radar emitter signal identification, where the bispectrum estimation of rada...
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Article
Pairwise Constrained Fuzzy Clustering: Relation, Comparison and Parallelization
Although clustering with pairwise constraints through penalty regularization has been widely adopted in existing semi-supervised clustering approaches, little work has been done on theoretical comparison of th...
