Selective Feature Fusion Based Adaptive Image Segmentation Algorithm by Qianwen Li, Zhihua Wei, Wen Shen

“…Specifically, the proposed method fuses selected features and applies the fused features to region growing segmentation algorithm. …”
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Analysis of selected features of application based on monolithic and microservice architecture by Kamil Jaskot, Sławomir Przyłucki

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SELECTION FEATURES OF THE FIELDS REPRESENTATION FOR THE ADDITIONAL SOURCES OF THE PARTIAL DOMAINS by A.P. ZVEREV

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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

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Selected features of Philippine English pronunciation among three groups of Ilocano speakers by L. I Haloc, S. N Dita

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Selected features of Philippine English pronunciation among three groups of Ilocano speakers by L. I Haloc, S. N Dita

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Elderly Patient Management Problems: Antithrombotic Therapy Selection Features. Clinical Case by D. U. Akasheva, E. S. Bulgakova, I. S. Yavelov, A. Yu. Gorshkov, O. M. Drapkina

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Integrating SNP data to reveal the adaptive selection features of goat populations in extreme environments by Wannian Wang, Ke Cai, Mengdan Fan, Zhixu Pang, Yangyang Pan, Lifen Cheng, Liying Qiao, Ruizhen Wang, Wenzhong Liu, Jianhua Liu

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Acute lymphoblastic leukemia diagnosis using machine learning techniques based on selected features by Enas M.F. El Houby

“…Three classifiers which are Naïve Bayes (NB), Support Vector Machine (SVM) and K-nearest Neighbor (K-NN) were utilized to classify the images based on selected features. Ant Colony Optimization (ACO) was combined with the classifiers as a feature selection method to identify the optimal subset of features among the extracted features from segmented cell parts that yield the highest classification accuracy. …”
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Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

“…In the neck, a multi-layer selective feature fusion pyramid (MS-FPN) is constructed to perform attention-based filtering on high-level semantic features and low-level spatial details, followed by feature enhancement via multiplication and global semantic refinement through residual connections. …”
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Selective Feature Sets Based Fake News Detection for COVID-19 to Manage Infodemic by Manideep Narra, Muhammad Umer, Saima Sadiq, Ala' Abdulmajid Eshmawi, Hanen Karamti, Abdullah Mohamed, Imran Ashraf

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An efficient leukemia prediction method using machine learning and deep learning with selected features. by Mahwish Ilyas, Muhammad Ramzan, Mohamed Deriche, Khalid Mahmood, Anam Naz

“…The proposed approach utilizes the 25 most differentiating selected features for classification using machine and deep learning techniques. …”
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Variability-Aware Machine Learning Model Selection: Feature Modeling, Instantiation, and Experimental Case Study by Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

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DNS over HTTPS Tunneling Detection System Based on Selected Features via Ant Colony Optimization by Hardi Sabah Talabani, Zrar Khalid Abdul, Hardi Mohammed Mohammed Saleh

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Hybrid Methods Random Forest and FOX-Inspired Optimization Algorithm for Selecting Features in Cervical Cancer Data by Afidatul Masbakhah, Umu Sa'adah, Mohamad Muslikh

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Data-centric automated approach to predict autism spectrum disorder based on selective features and explainable artificial intelligence by Asma Aldrees, Stephen Ojo, James Wanliss, Muhammad Umer, Muhammad Attique Khan, Bayan Alabdullah, Shtwai Alsubai, Nisreen Innab

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Probabilistic prediction intervals of short-term wind speed using selected features and time shift dependent machine learning models by Rami Al-Hajj, Gholamreza Oskrochi, Mohamad M. Fouad, Ali Assi

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From Baseline to Best Practice: An Advanced Feature Selection, Feature Resampling and Grid Search Techniques to Improve Injury Severity Prediction by Soukaina EL Ferouali, Zouhair Elamrani Abou Elassad, Sara Qassimi, Abdelmounaîm Abdali

“…Compared to comparable systems without feature selection, feature resampling, and optimization methods, the results demonstrate that employing optimized XGBoost along with grid search in conjunction with SelectKBest and SMOTE strategy has resulted in greater performance, with an 89% R2 score. …”
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Comparing large scale and selected feature learning for community acquired pneumonia prognosis prediction using clinical data: a stacked ensemble approach by Ji Hyun Lee, Hyun Woo Lee, Hyo Jin Lee, Tae Yun Park, Kwang Nam Jin, Dong Hyun Kim, Borim Ryu

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Research on Inspection Method of Intelligent Factory Inspection Robot for Personnel Safety Protection by Ruohuai Sun, Bin Zhao, Chengdong Wu, Xiaohong Qin

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