Exploring visitor perception of Asian historic districts through deep learning and social media data by Yinying Tao, Yifeng Jiang, Manshu Huang, Kai Zhou

“…This study utilizes advanced deep learning techniques and sentiment analysis to assess visitor perceptions of the Xiaohe Straight Street Cultural and Historical District in Hangzhou, a site undergoing efforts of preservation and revitalization. …”
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A Review of Data-Driven Models for Electromagnetic Devices Design and Analysis by Zihan Li, Mengyu Cheng, Andy Tyrrell, Xing Zhao

“…This review, focusing on recent deep learning advances, presents a comprehensive review on the application of data-driven models in the design and optimization of electromagnetic devices, summarizing the statistical models such as Response Surface Methodology (RSM) and recent popular machine learning (ML) methods in handling multiple variables, as well as the deep learning (DL) models, in predicting various electromagnetic device parameters and optimizing electromagnetic models. …”
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Data normalization in machine learning by V. V. Starovoitov, Yu. I. Golub

“…In machine learning, the input data is often given in different dimensions. …”
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Analyzing the Impact of Data Augmentation on the Explainability of Deep Learning-Based Medical Image Classification by Xinyu (Freddie) Liu, Gizem Karagoz, Nirvana Meratnia

“…Deep learning models are widely used for medical image analysis and require large datasets, while sufficient high-quality medical data for training are scarce. …”
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Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

“…The findings gained from this empirical analysis provide valuable direction for enhancing the design of adversarial attack algorithms, thereby advancing adversarial machine learning on tabular data.…”
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FADLEC: feature extraction and arrhythmia classification using deep learning from electrocardiograph signals by Sumita Lamba, Satender Kumar, Manoj Diwakar

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Gravitational search algorithm‐extreme learning machine for COVID‐19 active cases forecasting by Boyu Huang, Youyi Song, Zhihan Cui, Haowen Dou, Dazhi Jiang, Teng Zhou, Jing Qin

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Markov-CVAELabeller: A Deep Learning Approach for the Labelling of Fault Data by Christian Velasco-Gallego, Nieves Cubo-Mateo

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Cloud Removal in Full-disk Solar Images Using Deep Learning by Zhenhong Shang, Peng Du, Zhenping Qiang, Runxin Li

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Deep-learning based colorectal cancer pathological analysis with hyperspectral light field microscopy by Hao Sheng, Yingying Zhang, Ruixuan Cong, Shuai Wang, Da Yang, Zhenglong Cui, Xuefei Huang, Rongshan Chen, Jiapeng Liu, Wei Ke, Weifeng Lv

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Community Detection Framework Using Deep Learning in Social Media Analysis by Ao Shen, Kam-Pui Chow

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Editorial: Application of novel statistical and machine-learning methods to high-dimensional clinical cancer and (multi-) omics data volume II by Chao Xu, Shaolong Cao, Md Ashad Alam

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A scoping review and bibliometric analysis (ScoRBA) of machine learning in genetic data analysis: unveiling the transformative potential by Zakaria et al.

“…This study uses scoping review and bibliometric analysis; ScoRBA, to comprehensively highlight the recurrent themes linked to machine learning (ML) applications in genetic data analytics. …”

Recognition of anxiety and depression using gait data recorded by the kinect sensor: a machine learning approach with data augmentation by Milad Shoryabi, Ahmad Hajipour, Afshin Shoeibi, Ali Foroutannia

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Machine Learning and data mining tools applied for databases of low number of records by Hubert Anysz

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Functional Data Analysis for Prediction of Employee Presence by Nouhaila Goujili, Matthieu Saumard, Nicolas Cochard, Maher Jridi

“…Finally, we contrast this method with other models widely used in time series analysis, Seasonal Autoregressive Integrated Moving Average with Exogenous Regressors (SARIMAX), Long Short Term Memory (LSTM), Adaboost, and Deep Learning for functional data analysis (DFMM). …”
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Evaluation of Bayesian network scoring functions in polychotomous data analysis by Xuejia Ke, Katherine Keenan, V. Anne Smith

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Okra disease dataset for classification and segmentation: Dataset collection, analysis and applicationsMendeley DataMendeley Data by K. Sowmiya, M. Thenmozhi

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Data-driven models for significant wave height forecasting: Comparative analysis of machine learning techniques by Ahmet Durap

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Analysis of machine learning approaches for the interpretation of acoustic fields obtained by well noise data modelling by N. V. Mutovkin

“…Assessing the phase composition of the fluid in a well based analysis of the frequencies of the radial resonance modes excited by acoustic noise in the inflow zone is a promising method for interpreting the results of passive noise metering. …”
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