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Shumin Lai, Longjun Huang, Ping Li, Zhenzhen Luo, Jianzhong Wang and Yugen Yi
In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve the p...
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Meng Wu and Pudong Shi
To address the problem of poor detection and under-utilization of the spatial relationship between nodes in human pose estimation, a method based on an improved spatial temporal graph convolutional network (ST-GCN) model is proposed. Firstly, upsampling ...
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Taki Hasan Rafi and Young-Woong Ko
Electrocardiography (ECG)-based arrhythmia classification intends to have a massive role in cardiovascular disease monitoring and early diagnosis. However, ECG datasets are mostly imbalanced and have regularization to use real-time patient data due to pr...
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Viacheslav Moskalenko, Vyacheslav Kharchenko, Alona Moskalenko and Sergey Petrov
Modern trainable image recognition models are vulnerable to different types of perturbations; hence, the development of resilient intelligent algorithms for safety-critical applications remains a relevant concern to reduce the impact of perturbation on m...
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Olga Kostyukova and Tatiana Tchemisova
In this paper, we continue an earlier study of the regularization procedures of linear copositive problems and present new algorithms that can be considered as modifications of the algorithm described in our previous publication, which is based on the co...
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Reza Soleimani and Edgar Lobaton
Physiological and kinematic signals from humans are often used for monitoring health. Several processes of interest (e.g., cardiac and respiratory processes, and locomotion) demonstrate periodicity. Training models for inference on these signals (e.g., d...
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Kemal Güven and Andaç Töre Samiloglu
Neural networks are one of the methods used in system identification problems. In this study, a NARX network with a serial-parallel structure was used to identify an unknown aerial delivery system with a ram-air parachute. The dataset was created using t...
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Yanwei Sun, Shirin Malihi, Hao Li and Mehdi Maboudi
Windows, as key components of building facades, have received increasing attention in facade parsing. Convolutional neural networks have shown promising results in window extraction. Most existing methods segment a facade into semantic categories and sub...
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Xiaobin Yuan, Jingping Zhu and Xiaobin Li
Blind image deblurring tries to recover a sharp version from a blurred image, where blur kernel is usually unknown. Recently, sparse representation has been successfully applied to estimate the blur kernel. However, the sparse representation has not cons...
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Mattia Zanon, Giuliano Zambonin, Gian Antonio Susto and Seán McLoone
In knowledge-based systems, besides obtaining good output prediction accuracy, it is crucial to understand the subset of input variables that have most influence on the output, with the goal of gaining deeper insight into the underlying process. These re...
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