AFQSeg: An Adaptive Feature Quantization Network for Instance-Level Surface Crack Segmentation by Shaoliang Fang, Lu Lu, Zhu Lin, Zhanyu Yang, Shaosheng Wang

“…The trainable crack post-processing module incorporates edge-guided post-processing algorithms to correct false predictions and refine segmentation results. …”
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Diagnostic framework to validate clinical machine learning models locally on temporally stamped data by Maximilian Schuessler, Scott Fleming, Shannon Meyer, Tina Seto, Tina Hernandez-Boussard

“…Finally, feature importance and data valuation algorithms are applied for feature reduction and data quality assessment. …”
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Comprehensive Analysis of the Influence of Technical and Biological Variations on De Novo Assembly of RNA-Seq Datasets by Gonzalez Sergio Alberto, Rivarola Maximo, Ribone Andres, Lew Sergio, Paniego Norma

“…This selection will affect the completeness of represented genes and assembled isoforms, as well as contribute to error reduction.…”
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SFMattingNet: A Trimap-Free Deep Image Matting Approach for Smoke and Fire Scenes by Shihui Ma, Zhaoyang Xu, Hongping Yan

“…Since image matting algorithms compute these alpha values, the quality of the alpha composition directly depends on the performance of the smoke and fire matting methods. …”
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Automatic Extraction and Visualization of Interaction Networks for German Fairy Tales by David Schmidt, Frank Puppe

“…After an evaluation of the individual algorithms, the predicted networks are evaluated against benchmarks established by networks based on manually annotated coreference and speaker/addressee information. …”
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Application of Machine Learning for Real-Time Phishing Attack Detection by Akshay Shankar Agrawal, Sanketi Raut, Andrina Dsouza, Jimit Mehta, Prajwal Naik

“…The system uses machine learning algorithms to distinguish legitimate websites from phishing websites and generate a prediction to be used for the platform. …”
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Diagnosis of knee meniscal injuries using artificial intelligence: A systematic review and meta-analysis of diagnostic performance. by Soheil Mohammadi, Ali Jahanshahi, Mohammad Shahrabi Farahani, Mohammad Amin Salehi, Negin Frounchi, Ali Guermazi

“…The included studies' reporting quality and risk of bias were evaluated using the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) and the Prediction Model Study Risk of Bias Assessment Tool (PROBAST), respectively. …”
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End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality by Tingting Zhang, Jing Li, Jinpeng Tong, Yihu Song, Li Wang, Renye Wu, Xuan Wei, Yuanyuan Song, Rensen Zeng

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Planeación asistida por computadora del proceso tecnológico de ensamble. //Computer-aided gliding of the assembles technological process. by L. L. Tomás García, R. L. Ávila Rondón

“…The generated assembly sequences are preprocessed<br />and optimized for the assembly Process Planning using Genetic Algorithms. This approach integrates the geometric and<br />technological information of the assembly process, which allows reducing the number of elements and sequences to be<br />processed with the consequent processing time and cost reduction.…”
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A novel approach for snow depth retrieval in forested areas by integrating horizontal and vertical canopy structures information by Shanna Yue, Liyun Dai, Jie Deng, Yanxing Hu, Lin Xiao, Tao Che

“…Compared to the Chang algorithm and the AMSR-E snow depth product, this study demonstrated higher accuracy in the mid- to high-latitude forested areas of Eurasia, with an R value approximately twice as high and a reduction in the overall root mean square error (RMSE) by 2.3 cm and 7.2 cm, respectively. …”
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Comparison of Machine Learning and Statistical Approaches of Detecting Anomalies Using a Simulation Study by Klaudia Lenart

“…Results: While the accuracy of the statistical methods was dependent on the precise prediction of the percentage of the anomalies that would occur in the data, the machine learning algorithms’ recall was significantly lower when the change in the marginal distribution of the value parameters was smaller. …”
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Sex estimation with ensemble learning: an analysis using anthropometric measurements of piriform aperture by Muhammed Emin Parlak, Yasin Etli, Murat Beyhan, Kubilay Kanat, Hüseyin Alper Kızıloğlu

“…Results Sex prediction results were obtained with a maximum accuracy of 76.5% with discriminant analysis, 84.2% with machine learning algorithms, and 85.7% with the ensemble learning method. …”
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Elevation of transaminases. What if not the liver? by I. V. Sharkova

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Deep Learning-Based Multitarget Motion Shadow Rejection and Accurate Tracking for Sports Video by Chunxia Duan

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Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

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From Backtracking To Deep Learning: A Survey On Methods For Solving Constraint Satisfaction Problems by Fatima AIT HATRIT, Kamal AMROUN

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Mechanisms for Secure Access to Data of Scientometric Systems Using Virtual DBMS by Alexander Kozitsin, Maxim Zanchurin

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Searching for Similar Subgraphs in an Unweighted Undirected Graph by Computing Isomorphic Path Sets by Valentin Sysoev, Aleksandr Bykov

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An Inductive Logical Model with Exceptional Information for Error Detection and Correction in Large Knowledge Bases by Yan Wu, Xiao Lin, Haojie Lian, Zili Zhang

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