Improving deep convolutional neural networks with mixed maxout units by Hui-zhen ZHAO, Fu-xian LIU, Long-yue LI, Chang LUO

Subjects: “…deep learning…”
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Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…An integrated machine learning framework, combining 12 algorithms was used to construct a PCDS model. …”
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Instantaneous Metabolic Energetics: Data-Driven Modeling Using Function-Based Surrogates and Gradient Boosting by Christopher Buglino, William Z. Peng, Stacy Ashlyn, Hyunjong Song, Howard J. Hillstrom, Joo H. Kim

“…A gradient-boosted machine-learning model was then trained on the surrogate functions’ outputs. …”
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Taxonomic hierarchical loss function for enhanced crop and weed phenotyping in multi-task semantic segmentation by Artzai Picon, Daniel Mugica, Itziar Eguskiza, Arantza Bereciartua-Perez, Javier Romero, Carlos Javier Jimenez, Christian Klukas, Laura Gomez-Zamanillo, Till Eggers, Ramon Navarra-Mestre

“…The proposed loss function support datasets with varying granularity and annotation heterogeneity, including for partial annotations at the pixel level. …”
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ON THE EXPEDIENCY AND DIRECTIONS OF IMPROVING THE METHODOLOGY OF TEACHING STUDENTS MATERIAL OF THE CONTENT LINE "FUNCTIONS AND THEIR GRAPHS" by Тетяна Года, Олександр Школьний

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Prediction of Soil Field Capacity and Permanent Wilting Point Using Accessible Parameters by Machine Learning by Liwei Liu, Xingmao Ma

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Correlations Between Cognitive and Social Functioning of Schoolchildren: Study of Population Data Using methods of intellectual Analysis of heterogeneous Data by Leyla S. Namazova-Baranova, Georgiy A. Karkashadze, Elena A. Vishnyova, A. I. Molodchenko

Subjects: “…machine learning…”
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A model of digital transformation of the learning process in higher education by Olga V. Ivanova

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Deep learning-based feature selection for detection of autism spectrum disorder by Ibrahim Nafisah, Nermine Mahmoud, Ahmed A. Ewees, Mohamed G. Khattap, Abdelghani Dahou, Safar M. Alghamdi, Ibrahim A. Fares, Mohammed Azmi Al-Betar, Mohammed Azmi Al-Betar, Mohamed Abd Elaziz, Mohamed Abd Elaziz

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Learning Constitutive Relations From Soil Moisture Data via Physically Constrained Neural Networks by Toshiyuki Bandai, Teamrat A. Ghezzehei, Peishi Jiang, Patrick Kidger, Xingyuan Chen, Carl I. Steefel

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Study of Heart Rate Variability to Comprehend the Significance of Singing Bowl Meditation on the Functioning of the Autonomic Nervous System by Ritika Upadhyay, Biswajeet Champaty, Suraj Kumar Nayak

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Analysis of Electron Distribution Functions From the Magnetospheric Multiscale (MMS) Mission Using the Gaussian Mixture Model by Beniamino Sanò, Nathan N. Maes Anno, David L. Newman, Marty Goldman, Francesco Valentini, Denise Perrone, Giovanni Lapenta

Subjects: “…unsupervised machine learning…”
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Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging by Saurabh Bhattacharya, Sashikanta Prusty, Sanjay P. Pande, Monali Gulhane, Santosh H. Lavate, Nitin Rakesh, Saravanan Veerasamy

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Deep Reinforcement Learning for Control of Time-Varying Musculoskeletal Systems With High Fatigability: A Feasibility Study by Jessica Abreu, Douglas C. Crowder, Robert F. Kirsch

Subjects: “…Reinforcement learning…”
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Evaluation of Rehabilitation Outcomes in Patients with Chronic Neurological Health Conditions Using a Machine Learning Approach by Gabriele Santilli, Massimiliano Mangone, Francesco Agostini, Marco Paoloni, Andrea Bernetti, Anxhelo Diko, Lucrezia Tognolo, Daniele Coraci, Federico Vigevano, Mario Vetrano, Maria Chiara Vulpiani, Pietro Fiore, Francesca Gimigliano

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MOMFNet: A Deep Learning Approach for InSAR Phase Filtering Based on Multi-Objective Multi-Kernel Feature Extraction by Xuedong Zhang, Cheng Peng, Ziqi Li, Yaqi Zhang, Yongxuan Liu, Yong Wang

“…This research provides important insights into the application of deep learning for InSAR denoising.…”
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Multi-Functional Optical Spectrum Analysis Using Multi-Task Cascaded Neural Networks by Haoyu Wang, Sheng Cui, Changjian Ke, Chenglong Yu, Zi Liang, Deming Liu

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The Use of Neural Networks in Distance Education Technologies for the Identification of Students by O. A. Kozlova, A. A. Protasova

Subjects: “…distance learning…”
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Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model by Sadra Shadkani, Yousef Hemmatzadeh, Amirreza Pak, Soroush Abolfathi

“…The proposed framework integrates feedforward neural networks (FFNN), long short-term memory (LSTM) networks, stochastic gradient descent (SGD), and radial basis function (RBF) models, augmented with a first-order differencing technique. …”
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Exact Expressions for Kullback–Leibler Divergence for Univariate Distributions by Victor Nawa, Saralees Nadarajah

“…The derived expressions incorporate various special functions, highlighting the mathematical complexity and richness of the topic. …”
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