Results 11 to 20 of about 59,031 (278)
Lightweight Gearbox Fault Diagnosis Under High Noise Based on Improved Multi-Scale Depthwise Separable Convolution and Efficient Channel Attention [PDF]
SensorsGearbox fault diagnosis under strong-noise conditions remains challenging due to the difficulty of extracting weak fault-related features from noise-dominated vibration signals, inefficient modeling of multi-scale impulsive characteristics under limited ...
Xiubin Liu +4 more
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The Dirichlet divisor problem over square-free integers and unitary convolutions [PDF]
Notes on Number Theory and Discrete Mathematics, 2023 We obtain an asymptotic formula for the sum ~D₂ of the divisors of all square-free integers less than or equal to x, with error term O(x^{1/2 + ε}). This improves the error term O(x^{3/4 + ε}) presented in [7] obtained via analytical methods.
André Pierro de Camargo
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Approximation of Free Convolutions by Free Infinitely Divisible Laws [PDF]
Theory of Probability & Its Applications, 2021 Основываясь на методе сyбoрдинационных функций, мы получаем оценки минимальных ошибок аппроксимации $n$-кратных свободных сверток вероятностных мер безгранично делимыми свободными вероятностными мерами.
Chistyakov, Gennadiy, Götze, Friedrich
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DMPCONV: DECOUPLING MULTI-BRANCH POINTWISE CONVOLUTIONS FOR LIGHT-WEIGHT REMOTE SENSING SCENE CLASSIFICATION [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 The use of multi-branch architectures in off-the-shelf light-weight residual series neural networks can significantly improve their performance in remote sensing scene classification tasks.
J. Hou +13 more
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Adaptive Image Dehazing Algorithm Based on Dynamic Convolution Kernels [PDF]
Jisuanji kexue, 2023 Existing image dehazing methods generally have problems such as incomplete dehazing and color distortion.Image dehazing methods based on traditional deep learning models mostly use static inference during testing,which use the same and fixed parameters ...
LIU Zhe, LIANG Yudong, LI Jiaying
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A Context-Free Grammar Associated with Fibonacci and Lucas Sequences
Journal of Mathematics, 2023 We introduce a context-free grammar G=s⟶s+d,d⟶s to generate Fibonacci and Lucas sequences. By applying the grammar G, we give a grammatical proof of the Binet formula.
Harold Ruilong Yang
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Cumulants for finite free convolution [PDF]
Journal of Combinatorial Theory, Series A, 2018 In this paper we define cumulants for finite free convolution. We give a moment-cumulant formula and show that these cumulants satisfy desired properties: they are additive with respect to finite free convolution and they approach free cumulants as the dimension goes to infinity.
Octavio Arizmendi, Daniel Perales
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Diyala Journal of Engineering Sciences, 2022 In this study, MATLAB code was used to analyze the natural frequency in two types of U-shape metal expansion bellows with various supporting conditions (fixed-fixed and fixed- free).
Mustafa Sabri Mohammed, Dhia A. Salal
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Exemplar-Free Continual Transformer with Convolutions
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 Continual Learning (CL) involves training a machine learning model in a sequential manner to learn new information while retaining previously learned tasks without the presence of previous training data. Although there has been significant interest in CL, most recent CL approaches in computer vision have focused on convolutional architectures only ...
Anurag Roy +5 more
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Fluids, 2023 This study presents a comprehensive analysis of the second-order perturbation theory applied to the Navier–Stokes equations governing free surface flows.
Arash Ghahraman, Gyula Bene
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