Online Persian/Arabic Writer Identification using Gated Recurrent Unit Neural Networks by Mahsa Aliakbarzadeh, Farbod Razzazi

“…Conventional methods in writer identification mostly rely on hand-crafted features to represent the characteristics of different handwritten scripts. …”
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Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

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Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome by Pedro Pons-Suñer, François Signol, Noemi Alvarez, Claudia Sargas, Sara Dorado, Jose Vicente Gil Ortí, Juan A. Delgado Sanchis, Marta Llop, Laura Arnal, Rafael Llobet, Juan-Carlos Perez-Cortes, Rosa Ayala, Eva Barragán

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Fault Diagnosis of Induction Motors Using Recurrence Quantification Analysis and LSTM with Weighted BN by Dengyu Xiao, Yixiang Huang, Chengjin Qin, Haotian Shi, Yanming Li

“…To cover those shortcomings, in this paper, two manual feature learning approaches are embedded into a deep learning algorithm, and thus, a novel fault diagnosis framework is proposed for three-phase induction motors with a hybrid feature learning method, which combines empirical statistical parameters, recurrence quantification analysis (RQA) and long short-term memory (LSTM) neural network. …”
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Categorical Cross-Recurrence Quantification Analysis Applied to Communicative Interaction during Ainsworth’s Strange Situation by Danitza Lira-Palma, Karolyn González-Rosales, Ramón D. Castillo, Rosario Spencer, Andrés Fresno

“…The metrics were estimated through a Categorical Cross-Recurrence Quantification Analysis applied to the behaviours of individuals and dyads. …”
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Convolutional Recurrent Neural Networks for Observation-Centered Plant Identification by Xuanxin Liu, Fu Xu, Yu Sun, Haiyan Zhang, Zhibo Chen

“…To tolerate the significant intraclass variances, the convolutional recurrent neural networks (C-RNNs) are proposed for observation-centered plant identification to mimic human behaviors. …”
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A Differential Biomarker Based on Recurrence Quantification Analysis of EEG Signal and Genetic Algorithm for Epilepsy Diagnosis by Vanithamani Palanisamy, A Ranichitra, Radhamani Ellapparaj

“…Among 12 calculated RQA features from EEGs, the features of longest diagonal line, transitivity and the recurrence rate with 6, 4 and 3 numbers of 100% accuracy in separating normal and epileptic EEGs yielded better results than other recurrence features. …”
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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep learning model optimization. …”
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Sliding Recurrence Analysis and its Application of Gear Vibration Signal by Xiao Han, Lv Yong

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Study on incentive mechanism of reward and punishment on work efficiency of PCB welder based on recurrence quantification analysis and electroencephalogram signals by Zhang Qian, Mingyue Guo, Fuwang Wang

“…To address this issue, this study innovatively combines recurrence quantification analysis (RQA) with electroencephalogram (EEG) signals, proposing a dynamic incentive evaluation model based on the analysis of brain chaos characteristics. …”
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Application of Recurrent Neural Networks in Uncertainty Analysis of Sheet Metal Forming by Cruz Daniel, Parreira Tomás, Marques Armando, Prates Pedro, Oliveira Marta, Neto Diogo, Santos Abel, Amaral Rui, Barbosa Manuel, Pereira André

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Hybrid Optimized Feature Selection and Deep Learning Method for Emotion Recognition That Uses EEG Data by asmaa Bashar Hmaza, Rajaa K. Hasoun

“…First, particle swarm optimization (PSO) identifies and optimizes critical functions and reduces feature dimensionality. Thereafter, long short-term memory (LSTM), gated recurrent unit (GRU), and simple recurrent neural network (RNN) architectures are used in emotion identification. …”
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Corrosion type identification in flanged joints using recurrent neural networks on electrochemical noise measurements by Soroosh Hakimian, Abdel-Hakim Bouzid, Lucas A. Hof

“…Electrochemical noise (EN) measurements can detect such corrosion, yet processing EN data is time-consuming and requires expertise. This study applies recurrent neural networks (RNNs) to automate corrosion type identification on flange surfaces using raw EN signals from spontaneous electrochemical reactions. …”
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Gas Leak Detection and Leakage Rate Identification in Underground Utility Tunnels Using a Convolutional Recurrent Neural Network by Ziyang Jiang, Canghai Zhang, Zhao Xu, Wenbin Song

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Risk Factors and Vascular Features Associated With Local Recurrence in Pancreatic Cancer Post‐Pancreaticoduodenectomy: A Retrospective Cohort Study by Ting‐Kai Liao, Ying Jui Chao, Wei‐Hsun Lu, Ping‐Jui Su, Chih‐Jung Wang, Yan‐Shen Shan

“…This study highlights potential risk factors, recurrence patterns, and associated vascular features for early identification. …”
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Deep learning for predicting invasive recurrence of ductal carcinoma in situ: leveraging histopathology images and clinical featuresResearch in context by Shannon Doyle, Esther H. Lips, Eric Marcus, Lennart Mulder, Yat-Hee Liu, Francesco Dal Canton, Timo Kootstra, Maartje M. van Seijen, Ihssane Bouybayoune, Elinor J. Sawyer, Alastair M. Thompson, Sarah E. Pinder, Clara I. Sánchez, Jonas Teuwen, Jelle Wesseling, Jelle Wesseling, Jos Jonkers, Jacco van Rheenen, Esther H. Lips, Marjanka Schmidt, Lodewyk F.A. Wessels, Proteeti Bhattacharjee, Alastair Thompson, Serena Nik-Zainal, Helen Davies, Elinor J. Sawyer, Andrew Futreal, Nicholas Navin, E. Shelley Hwang, Fariba Behbod, Daniel Rea, Hilary Stobart, Deborah Collyar, Donna Pinto, Ellen Verschuur, Marja van Oirsouw

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Identification of dominant instability modes in power systems based on spatial‐temporal feature mining and TSOA optimization by Miao Yu, Jianqun Sun, Shuoshuo Tian, Shouzhi Zhang, Jingjing Wei, Yixiao Wu

“…Firstly, spatio‐temporal feature mining is conducted, where convolutional neural networks are employed to learn crucial local features of transient curves, and bidirectional gated recurrent unit s utilized to learn transient features over time sequences. …”
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Who benefits from adjuvant chemotherapy? Identification of early recurrence in intrahepatic cholangiocarcinoma patients after curative-intent resection using machine learning algor... by Qi Li, Hengchao Liu, Yubo Ma, Zhenqi Tang, Chen Chen, Dong Zhang, Zhimin Geng

“…ObjectiveIt is vital to enhance the identification of early recurrence in intrahepatic cholangiocarcinoma (ICC) patients after curative-intent resection and to determine which patients could benefit from adjuvant chemotherapy (ACT). …”
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A Multi-Granularity Features Representation and Dimensionality Reduction Network for Website Fingerprinting by Yaojun Ding, Bingxuan Hu

“…The LRCT network effectively leverages the temporal learning advantages of Local Recurrent Networks (Local RNN) and the spatial learning strengths of Convolutional Neural Network (CNN) by designing the local feature extraction block (denoted as LRC Block), which extracts fine-grained local features from 2000-dimensional original sequences and reduces the dimensionality to 125. …”
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Decoding Pain Dynamics: EEG Insights into Neural Responses and Classification via RQA Analysis by Mahsa Tavasoli, Zahra Einalou, Reza Akhondzadeh

“…For this purpose, at the first step phasic pain is produced using coldness, then dynamical features via EEG are analyzed via Recurrence Quantification Analysis (RQA) method and finally Rough neural network classifier has been used for achieving accuracy to detect and categorize pain and non-pain states. …”
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