A Revised Counter-Propagation Network Model Integrating Rough Set for Structural Damage Detection by Shao-Fei Jiang, Chun Fu, Chun-Ming Zhang, Zhao-Qi Wu

“…This paper proposes a revised counter-propagation network (CPN) model by integrating rough set in structural damage detection, applicable for processing redundant and uncertain information as well as assessing structural health states. …”
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Accurate Feature Extraction from Historical Geologic Maps Using Open-Set Segmentation and Detection by Aaron Saxton, Jiahua Dong, Albert Bode, Nattapon Jaroenchai, Rob Kooper, Xiyue Zhu, Dou Hoon Kwark, William Kramer, Volodymyr Kindratenko, Shirui Luo

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Domain Generalized Open-Set Fault Detection and Diagnosis for Belt Conveyor Systems With Prototype Learning by Jinyou Kim, Ilkyu Yi, Young-Joo Suh

“…To address these issues, we developed a FDD approach that integrates open-set recognition and domain generalization, leveraging multivariate sensor data. …”
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Improving performance of defect detection by setting skewed tolerance and joint tolerances in crimp force monitor by Liancheng Zeng, Dali Qin

“…Abstract A Crimp Force Monitor (CFM) detects defects by whether the crimp force curve of the force sensor exceeds the set tolerance, with the goal of low defect miss rate and false alarm rate. …”
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GCN-based unsupervised community detection with refined structure centers and expanded pseudo-labeled set. by Bing Guo, Liping Deng, Tao Lian

“…Community detection is a classical problem for analyzing the structures of various graph-structured data. …”
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The data dimensionality reduction and bad data detection in the process of smart grid reconstruction through machine learning. by Bo Yu, Zheng Wang, Shangke Liu, Xiaomin Liu, Ruixin Gou

“…To detect false data injection attacks (FDIAs) in power grid reconstruction and solve the problem of high data dimension and bad abnormal data processing in the power system, thereby achieving safe and stable operation of the power grid system, this study introduces machine learning methods to explore the detection of FDIAs. …”
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Deep learning for early detection of papillary bladder cancer on a limited set of cystoscopic images by V. S. Rozova, C. Russo, V. Y. Lekarev, V. V. Kazantseva, A. M. Dymov, A. S. Rzhevskiy, A. V. Zvyagin

“…The aim of this study was to develop and evaluate the effectiveness of a convolutional neural network (CNN) in detecting papillary bladder cancer (PBC) using a limited set of cystoscopic images.Materials and methods. …”
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Advancing malaria reactive case detection in a Zambia-like setting: A modeling study. by Chilochibi Chiziba, Japhet Chiwaula, Busiku Hamainza, Sheetal Silal

“…In Zambia-like settings, asymptomatic and clinical carriers not seeking treatment further complicate malaria elimination, making reactive case detection (RCD) essential for identifying undetected infections. …”
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MODAMS: design of a multimodal object-detection based augmentation model for satellite image sets by Rahul Malik, Rachit Garg, Korhan Cengiz, Nikola Ivković, Adnan Akhunzada

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Evaluation of commercial point-of-care glucometers for detection and monitoring of neonatal hypoglycemia in resource-constrained settings by Meaghan Bond, Elizabeth Asma, Joseph Peterson, Lauren Oparah, Millicent Alooh, Danica Kumara, Z. Maria Oden, Chinyere Ezeaka, Elizabeth Molyneux, Rebecca Richards-Kortum

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Enhancing Wearable Fall Detection System via Synthetic Data by Minakshi Debnath, Sana Alamgeer, Md Shahriar Kabir, Anne H. Ngu

“…Incorporating Diffusion-based synthetic data improves the offline F1-score by 7–10% and boosts real-time fall detection performance by 24%, confirming its value in enhancing model robustness and applicability in real-world settings.…”
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Leveraging generative adversarial networks for data augmentation to improve fault detection in wind turbines with imbalanced data by Subhajit Chatterjee, Yung-Cheol Byun

“…Notably, the disparity in dataset sizes among faults and the uneven distribution of fault classes pose a substantial obstacle in the realm of fault detection for wind turbines. This challenge is compounded by the time-intensive process required to amass sufficient fault data, setting it apart from more typical scenarios in the domain of wind turbines. …”
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Massive Data Processing Method for Battery Energy Storage Power Stations Based on Rough Sets by Juan CHEN, Dong HUI, Maosong FAN, Juan HU, Yongjin CHU

“…Given the above problems, the attributes of the data from a battery cluster are first reduced by the method using rough set theory. …”
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Classification of melanoma skin Cancer based on Image Data Set using different neural networks by Rukhsar Sabir, Tahir Mehmood

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A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization by Lizhi Cui, Zhihao Ling, Josiah Poon, Simon K. Poon, Junbin Gao, Paul Kwan

“…This paper proposes a separation method, based on the model of Generalized Reference Curve Measurement and the algorithm of Particle Swarm Optimization (GRCM-PSO), for the High Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD) data set. Firstly, initial parameters are generated to construct reference curves for the chromatogram peaks of the compounds based on its physical principle. …”
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Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets by Ricard Argelaguet, Britta Velten, Damien Arnol, Sascha Dietrich, Thorsten Zenz, John C Marioni, Florian Buettner, Wolfgang Huber, Oliver Stegle

“…However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi‐Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi‐omics data sets. …”
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Rill Erosion and Drainage Development in Post-Landslide Settings Using UAV–LiDAR Data by Xinyu Chen, Albertus Stephanus Louw, Ali P. Yunus, Saleh Alsulamy, Deha Agus Umarhadi, Md. Alamgir Hossen Bhuiyan, Ram Avtar

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Investigation of outlier detection algorithm by Vydūnas Šaltenis

“… The proposed outlier factor was used to analyze the multidimensional data sets regarding outlier detection. The paper describes two kinds of investigation: the influence of omitting some part of distances between data points, and the influence of additional (noisy) points to outlier detection quality.  …”
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A Survey of Zero-Shot Object Detection by Weipeng Cao, Xuyang Yao, Zhiwu Xu, Ye Liu, Yinghui Pan, Zhong Ming

“…This article provides a comprehensive review of the current state of ZSD, distinguishing four related methods—zero-shot, open-vocabulary, open-set, and open-world approaches—based on task objectives and data usage. …”
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An Optimally Oriented Coherence Attribute Method and Its Application to Faults and Fracture Sets Detection in Carbonate Reservoirs by Shuai Chen, Shengjun Li, Qi Ma, Lu Qin, Sanyi Yuan

“…Faults and fracture sets in carbonate reservoirs are key geological features that govern hydrocarbon migration, accumulation, and wellbore stability. …”
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