Cross-domain topic transfer learning method based on multiple balance and feature fusion by Zhenshun Xu, Zhenbiao Wang, Wenhao Zhang, Zengjin Tang

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Deep multi-view feature fusion with data augmentation for improved diabetic retinopathy classification by Boualleg Yaakoub, Daouadi Kheir Eddine, Guehairia Oussama, Djeddi Chawki, Cheddad Abbas, Siddiqi Imran, Bouderah Brahim

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Target Detection Algorithm Based on Global Feature Fusion in Parallel Dual Path Backbone by QIU Yunfei, XIN Hao

“…The active downsampling of the backbone of conventional single path architecture often leads to insufficient feature extraction and information loss. At the same time, simply adding or splicing feature pyramids is not conducive to the integration of shallow to deep features. …”
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Semi-Supervised Remote Sensing Building Change Detection with Joint Perturbation and Feature Complementation by Zhanlong Chen, Rui Wang, Yongyang Xu

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Local kernel renormalization as a mechanism for feature learning in overparametrized convolutional neural networks by R. Aiudi, R. Pacelli, P. Baglioni, A. Vezzani, R. Burioni, P. Rotondo

“…Abstract Empirical evidence shows that fully-connected neural networks in the infinite-width limit (lazy training) eventually outperform their finite-width counterparts in most computer vision tasks; on the other hand, modern architectures with convolutional layers often achieve optimal performances in the finite-width regime. …”
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Rapid estimation method of lithium battery state of health based on novel health feature by DONG Xiaohong, DONG Jinbo, WANG Mingshen, ZENG Fei, PAN Yi

“…Most data-driven lithium battery SOH estimation methods are computationally intensive and difficult to use in real-time in battery management system microcontrollers. …”
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Dynapenia and presarcopenia in patients with coronary atherosclerosis: clinical predictors and cardiac structural and functional features by A. G. Neeshpapa, V. N. Karetnikova, K. E. Krivoshapova, E. I. Karpova, A. N. Kokov, O. L. Barbarash

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Timeseries Fault Classification in Power Transmission Lines by Non-Intrusive Feature Extraction and Selection Using Supervised Machine Learning by Rab Nawaz, Hani A. Albalawi, Syed Basit Ali Bukhari, Khawaja Khalid Mehmood, Muhammad Sajid

“…Feature selection through dimensionality reduction techniques is used to improve model performance and more efficient use of computational resources. …”
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BAHGRF3: Human gait recognition in the indoor environment using deep learning features fusion assisted framework and posterior probability moth flame optimisation by Muhammad Abrar Ahmad Khan, Muhammad Attique Khan, Ateeq Ur Rehman, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Deepak Gupta, Saima Ahmed Rahin, Yudong Zhang

“…Both models are selected based on the top‐5 accuracy and less number of parameters. Later, both models are trained through deep transfer learning and extracted deep features fused using a voting scheme. …”
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DynaOOD-Net: Dynamic Progressive Feature Fusion and Energy Balancing for Robust Out-of-Distribution Detection by Jiting Zhou, Zhihao Zhou, Pu Zhang

“…Additionally, Dynamic Progressive Feature Pyramid Network-Lite (DP-FPN-Lite) is proposed, which reduces computational and storage overhead by simplifying the network architecture while preserving the core concepts of DP-FPN. …”
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Development and validation of a model based on preoperative dual-layer detector spectral computed tomography 3D VOI-based quantitative parameters to predict high Ki-67 proliferatio... by Dan Zeng, Jiayan Zhang, Zuhua Song, Qian Li, Dan Zhang, Xiaojiao Li, Youjia Wen, Xiaofang Ren, Xinwei Wang, Xiaodi Zhang, Zhuoyue Tang

“…Abstract Objective To develop and validate a model integrating dual-layer detector spectral computed tomography (DLCT) three-dimensional (3D) volume of interest (VOI)-based quantitative parameters and clinical features for predicting Ki-67 proliferation index (PI) in pancreatic ductal adenocarcinoma (PDAC). …”
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Analysis dynamic characteristics brushless motor of the mechatronic system in conditions of parametric uncertaintyby computer simulation methods by N. A. Malev, O. V. Pogoditsky, O. V. Kozelkov, A. M. Dyuryagin

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Radiomics Signatures Based on Computed Tomography for Noninvasive Prediction of CXCL10 Expression and Prognosis in Ovarian Cancer by Xiaohua Wang, Yuanyuan Xing, Xuan Zhou, Chunhui Wang, Shuyu Han, Sufen Zhao

“…For the data reduction, logistic regression, operator regression, least absolute shrinkage selection, radiomic feature construction, and feature selection were utilized. …”
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Comprehensive review on single-atom catalysts in electrochemical hydrogen-evolution reaction: computational modelling and experimental investigation by Fares Chabira, Sajjad Ali, Abbas Khan, Muhammad Humayun, Mohamed Bououdina

“…Single Atom Catalysts (SACs) have been recognised as promising catalysts for exceptional HER activities owing to their unique electronic and geometrical features. This comprehensive review highlights the effective correlation between computational modelling and experimental research in fabricating new SACs and better understanding their catalytic mechanisms in the HER. …”
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Assessing Sternal Dimensions for Sex Classification: Insights from a Greek Computed Tomography-Based Study by Konstantina Vatzia, Michail Fanariotis, Maciej Bugajski, Ioannis V. Fezoulidis, Maria Piagkou, Marianna Vlychou, George Triantafyllou, Ioannis Vezakis, George Botis, Stavroula Papadodima, George Matsopoulos, Katerina Vassiou

“…<b>Background/Objectives:</b> This study aimed to assess the potential of sternal morphometric parameters derived from multidetector computed tomography (MDCT) for sex estimation in a contemporary Greek population. …”
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Computer Simulation and Speedup of Solving Heat Transfer Problems of Heating and Melting Metal Particles with Laser Radiation by Arturas Gulevskis, Konstantin Volkov

“…The study of the process of laser action on powder materials requires the construction of mathematical models of the interaction of laser radiation with powder particles that take into account the features of energy supply and are applicable in a wide range of beam parameters and properties of the particle material. …”
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A division-dependent compartmental model for computing cell numbers in CFSE-based lymphocyte proliferation assays by H. Thomas Banks, W. Clayton Thompson, Cristina Peligero, Sandra Giest, Jordi Argilaguet, Andreas Meyerhans

“…From such a model, cell counts (in terms of the number of divisions undergone) can be directly computed and thus key biological parameters such as population doubling time and precursor viability can be determined. …”
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Enhancing the prediction of vitamin D deficiency levels using an integrated approach of deep learning and evolutionary computing by Ahmed Alzahrani, Muhammad Zubair Asghar

“…To improve the models effectiveness and guarantee the optimal choice of the features and hyper-parameters, we incorporate evolutionary computing methods, particularly genetic algorithms (GA). …”
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Evaluation of connection pool <i>PgBouncer</i> efficiency for optimizing relational database computing resources by A. S. Boronnikov, P. S. Tsyngalev, V. G. Ilyin, T. A. Demenkova

“…The research utilized methods of experimentation, induction, testing, and statistical analysis.Results. The main features, architecture and modes of operation of the PgBouncer service are considered. …”
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The hybrid feature extraction method for classification of adolescence idiopathic scoliosis using Evolving Spiking Neural Network by Nurbaity Sabri, Haza Nuzly Abdull Hamed, Zaidah Ibrahim, Kamalnizat Ibrahim, Mohd Adham Isa, Norizan Mat Diah

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