Results 161 to 170 of about 119,116 (212)
A first order method for linear programming parameterized by circuit imbalance. [PDF]
Math ProgramCole R, Hertrich C, Tao Y, Végh LA.
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A deep-SVM hybrid framework with enhanced EEG feature engineering and SHAP-based explainability for Alzheimer's classification. [PDF]
Sci RepAkbar F +5 more
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In Vivo Positron Emission Particle Tracking (PEPT) of Single Cells Using an Expectation Maximization Algorithm. [PDF]
IEEE Trans Med ImagingNguyen HTM, Das N, Nasiri R, Pratx G.
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A self-evolution cyber attack scheme generation system for cybersecurity evaluation. [PDF]
Sci RepYang M +6 more
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Nondestructive Detection of Eggshell Thickness Using Near-Infrared Spectroscopy Based on GBDT Feature Selection and an Improved CatBoost Algorithm. [PDF]
FoodsLi Z, Ji Y, Zhao C, Wang D, Zhou R.
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Mesh variational r-adaptivity for sharp modeling of brittle fracture
Dony G, Moës N, Remacle J.
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Russian language at school, 2022
The paper explores the metaphors and similes in modern literary text. The material for the study was V. O. Pelevin’s novel "The Invincible Sun" (2020).
O. Dimitrieva
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The paper explores the metaphors and similes in modern literary text. The material for the study was V. O. Pelevin’s novel "The Invincible Sun" (2020).
O. Dimitrieva
semanticscholar +1 more source
Research on influencing factors and path of digital transformation of manufacturing enterprises
Kybernetes, 2023PurposeUnder the influence of the digital economy, the digital transformation of manufacturing enterprises has attracted widespread attention from scholars at home and abroad due to its uniqueness and importance. However, the existing literature is still
Yue Zhang, Jiayuan Wang
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IEEE Workshop/Winter Conference on Applications of Computer Vision, 2023
Existing neural architecture search (NAS) methods comprise linear connected convolution operations and use ample search space to search task-driven convolution neural networks (CNN). These CNN models are computationally expensive and diminish the quality
Monu Verma +3 more
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Existing neural architecture search (NAS) methods comprise linear connected convolution operations and use ample search space to search task-driven convolution neural networks (CNN). These CNN models are computationally expensive and diminish the quality
Monu Verma +3 more
semanticscholar +1 more source