Novel Ensemble Approach with Incremental Information Level and Improved Evidence Theory for Attribute Reduction by Peng Yu, Yifeng Zheng, Ziwen Liu, Baoya Wei, Wenjie Zhang, Ziqiong Lin, Zhehan Li

“…Extracting the most distinguished attributes from complex datasets becomes a crucial problem. The existing attribute reduction approaches focus on the correlation between attributes and labels without considering the redundancy. …”
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Enhanced cloud removal via temporal U-Net and cloud cover evolution simulation by Qingwei Tong, Leiguang Wang, Qinling Dai, Chen Zheng, Fangrong Zhou

“…This method is applicable to all paired cloud datasets, enabling the construction of cloud evolution time-series in the absence of actual temporal information. …”
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Heavy and Lightweight Deep Learning Models for Semantic Segmentation: A Survey by Cristina Carunta, Alina Carunta, Calin-Adrian Popa

“…Additionally, some of the most popular datasets and performance metrics are presented. Further, we investigate the limitations of these methods, compare their performance on Pascal VOC 2012, Cityscapes, and ADE20K datasets, and finally indicate future research directions.…”
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Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review by Rizwan Riaz Mir, Nazeef Ul Haq, Kashif Ishaq, Nurhizam Safie, Abdul Basit Dogar

“…Multi-dimensional research questions covering complete diabetic management such as publication channels for diabetic research, existing machine learning solutions, physical activity tacking existing methods, and diabetic-associated datasets are included in this research. In this study, using a proper research protocol primary research articles related to diet, exercise, datasets, and blood analysis are selected and their quality is assessed for diabetic management. …”
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BenthicNet: A global compilation of seafloor images for deep learning applications by Scott C. Lowe, Benjamin Misiuk, Isaac Xu, Shakhboz Abdulazizov, Amit R. Baroi, Alex C. Bastos, Merlin Best, Vicki Ferrini, Ariell Friedman, Deborah Hart, Ove Hoegh-Guldberg, Daniel Ierodiaconou, Julia Mackin-McLaughlin, Kathryn Markey, Pedro S. Menandro, Jacquomo Monk, Shreya Nemani, John O’Brien, Elizabeth Oh, Luba Y. Reshitnyk, Katleen Robert, Chris M. Roelfsema, Jessica A. Sameoto, Alexandre C. G. Schimel, Jordan A. Thomson, Brittany R. Wilson, Melisa C. Wong, Craig J. Brown, Thomas Trappenberg

“…Abstract Advances in underwater imaging enable collection of extensive seafloor image datasets necessary for monitoring important benthic ecosystems. …”
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Rare Congenital Aberrant Left Superior Pulmonary Vein Discovered with Central Line Placement in a Patient with Critical Cardiorespiratory Collapse by Spencer Knox, Mario Madruga, S. J. Carlan

“…A 66-year-old male was found to have an anomalous left pulmonary vein when a central venous catheter was inserted for management of hypoxemia. …”
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News Topic Detection Based on Capsule Semantic Graph by Shuang Yang, Yan Tang

“…Experimental results on three standard datasets show that CSG can obtain higher precision, recall, and F1 values than several latest methods. …”
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Effects of Initial Drivers and Land Use on WRF Modeling for Near-Surface Fields and Atmospheric Boundary Layer over the Northeastern Tibetan Plateau by Junhua Yang, Keqin Duan

“…To improve the simulation performance of mesoscale models in the northeastern Tibetan Plateau, two reanalysis initial datasets (NCEP FNL and ERA-Interim) and two MODIS (Moderate-Resolution Imaging Spectroradiometer) land-use datasets (from 2001 and 2010) are used in WRF (Weather Research and Forecasting) modeling. …”
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Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

“…The proposed approach was tested on two datasets, with accuracy of 95% and 98%. Cross-validation yielded an average value of 0.99, and high values of Matthew's correlation coefficient (MCC) metrics of 0.96 and Cohen's Kappa (CK) of 0.96 confirmed the generalizability and reliability of the model. …”
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Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention by Fawaz Khaled Alarfaj, Shabnam Shahzadi

“…We can manage fraudulent activity in real-time and on dynamic datasets by utilizing deep learning algorithms, which allows for ongoing improvement of the fraud detection and prevention system.…”
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A New Truncated Muth Generated Family of Distributions with Applications by Abdullah M. Almarashi, Farrukh Jamal, Christophe Chesneau, Mohammed Elgarhy

“…The revised Weibull model is then used to fit two real-world datasets. The new model is shown to be more suited to these datasets than other competing models.…”
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Automation of historical weather data rescue by Y. Zhang, R. E. Sieber

“…We hope the workflow proposed can serve as a guideline that is easily replicable and can be utilized to transcribe other historical datasets.…”
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A New Transferable Fault Diagnosis Approach of Rotating Machinery Based on Deep Autoencoder and Dominant Features Selection under Different Operating Conditions by Fei Dong, Xiao Yu, Xinguo Shi, Ke Liu, Zhaoli Wu, Wanli Yu

“…Motor and bearing fault datasets are used for a series of experiments, and the results verify that the proposed methods have better cross-domain diagnosis performance than comparative models.…”
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Progressive Detection of Uncertainty in Natural Language Processing Using a Labeled Variable Dimension Kalman Filter by Lingaraj K., S. Supreeth, Yerriswamy T., Dayananda P., Rohith S., Shruthi G.

“…We iteratively upgraded the Kalman Filter to Labeled Variable Dimension Kalman Filter (LVDKF) based on observations from real datasets. The LVDKF learns two basic features from positive and negative words. …”
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Face presentation attack detection. A comprehensive evaluation of the generalisation problem by Artur Costa‐Pazo, Daniel Pérez‐Cabo, David Jiménez‐Cabello, José Luis Alba‐Castro, Esteban Vazquez‐Fernandez

“…Despite the success of several face‐PAD works in publicly available datasets, most of them fail to reach the market, revealing the lack of evaluation frameworks that represent realistic settings. …”
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A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data. by Lulu Pan, Qian Gao, Kecheng Wei, Yongfu Yu, Guoyou Qin, Tong Wang

“…Transfer learning aims to integrate useful information from multi-source datasets to improve the learning performance of target data. …”
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Research on the Classification of Traditional Building Materials in Southern Fujian Using the Reflection Intensity Values of Ground-Based LiDAR by Tsung-Chiang Wu, Neng-Gang Kuan, Wei-Cheng Lu

“…Ground-based LiDAR technology has been widely applied in various fields for acquiring 3D point cloud data, including spatial coordinates, digital color information, and laser reflectance intensities (I-values). These datasets preserve the digital information of scanned objects, supporting value-added applications. …”
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Convolutional Neural Networks for Software Defect Categorization: An Empirical Validation by Ruchika Malhotra, Madhukar Cherukuri

“…Extensive experiments were carried out on defect datasets from five Android operating system application modules, leading to the creation of 60 SDC models (5 datasets x 4 feature sets x 3 approaches). …”
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The role of chromatin state in intron retention: A case study in leveraging large scale deep learning models. by Ahmed Daoud, Asa Ben-Hur

“…Complex deep learning models trained on very large datasets have become key enabling tools for current research in natural language processing and computer vision. …”
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Maximizing the Accuracy of Continuous Quantification Measures Using Discrete PackTest Products with Deep Learning and Pseudocolor Imaging by Ryoichi Doi

“…The grayscale intensity values were used to prepare datasets for the ten and 83 (=10 + 73) images. For both datasets, chemical oxygen demand quantification was successful, resulting in values of normalized mean absolute error of less than 0.4% and coefficients of determination that were greater than 0.9996. …”
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