Multi‐stage image inpainting using improved partial convolutions by Cheng Li, Dan Xu, Hao Zhang

“…Some improvements are made on the partial convolutions to reduce artifacts like blurriness, which require a convolution kernel to contain known pixels more than a certain proportion. …”
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Hyperspectral Image Classification With Re-Attention Agent Transformer and Multiscale Partial Convolution by Junding Sun, Hongyuan Zhang, Jianlong Wang, Haifeng Sima, Shuanggen Jin

“…On the other hand, multiscale partial convolutions are utilized to further learn abstract spatial features. …”
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Partial Discharge Pattern Recognition of Switchgear Based on Residual Convolutional Neural Network by Xueyou HUANG, Jun XIONG, Yu ZHANG, Hui LIU, Lu CHEN, Xianglin MENG, Xiuchen JIANG

Subjects: “…convolutional neural network…”
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Application of the Algebraic Extension Method to the Construction of Orthogonal Bases for Partial Digital Convolutions by Aruzhan Kadyrzhan, Akhat Bakirov, Dina Shaltykova, Ibragim Suleimenov

“…As applied to partial convolutions, the Fourier–Galois transform is decomposed into a set of such transforms, each of which corresponds to operations in a certain Galois field. …”
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Small Object Detection Algorithm Based on Partial Convolution and Attention Fusion Detection Head by Peng Sheng, Zhu Fenghua, Zhou Jin, Zhu Gaofeng, Wang Yingxu, Chen Yuehui

Subjects: “…|small object detection|deep learning|partial convolution|attention mechanism|uav…”
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Identification method for wheel/rail tread defects based on integrated partial convolutional network by CHENG Xiang, HE Jing, ZHANG Changfan, JIA Lin

“…To address this challenge, an integrated partial convolutional network (I-PCNet) method was proposed for identifying wheel-rail tread defects. …”
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Physics-constrained convolutional neural networks for inverse problems in spatiotemporal partial differential equations by Daniel Kelshaw, Luca Magri

“…We propose a physics-constrained convolutional neural network (PC-CNN) to solve two types of inverse problems in partial differential equations (PDEs), which are nonlinear and vary both in space and time. …”
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Novel algorithm for multifocus image fusion: integration of convolutional neural network and partial differential equation by Gargi J Trivedi, Rajesh Sanghvi

Subjects: “…partial differential equation (pde)…”
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Self-Denoising of BOTDA Using Deep Convolutional Neural Networks by Di Qi, Chun-Kit Chan, Xun Guan

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Research on Partial Discharge Spectrum Recognition Technology Used in Power Cables Based on Convolutional Neural Networks by Zhenqing Zhang, Hao Wu, Weiyin Ren, Jian Yan, Zhefu Sun, Man Ding

Subjects: “…partial discharge…”
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A Dual-Branches Multiscale Dynamic Partial Convolutional Attention Network for Remote Sensing Change Detection by Wenbin Tang, Shuli Cheng, Anyu Du

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PhyICNet: Physics-informed interactive learning convolutional recurrent network for spatiotemporal dynamics by Ruohan Cao, Jin Su, Jinqian Feng, Qin Guo

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Basic properties of sumudu transformation and its application to some partial differential equations by Fatma Kaya, Yalçın Yılmaz

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Partial renal deletion of Klotho is not sufficient to impact renal electrolyte handling in distal convoluted tubule specific knock‐out mice by Teodora V. Grigore, Quinty M. Leusink, Malou Zuidscherwoude, Caro Bos, Hannes Olauson, Joost Hoenderop

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Accurate Identification Partial Discharge of Cable Termination for High-Speed Trains Based on S-Transform and Two-Dimensional Convolutional Network Algorithm by Yunlong Xie, Peng You, Guangning Wu, Tingyu Zhang, Yang Luo, Shuyuan Zhou, Kai Liu, Kui Chen, Dongli Xin, Guoqiang Gao

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PS-YOLO: A Lighter and Faster Network for UAV Object Detection by Han Zhong, Yan Zhang, Zhiguang Shi, Yu Zhang, Liang Zhao

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Partial-Net: A Method for Data Gaps Reconstruction on Mars Images by Depei Gu, Dingruibo Miao, Jianguo Yan, Zhigang Tu, Jean-Pierre Barriot

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Partial Discharge Type Identification of 10 kV T-Type Terminal Based on Empirical Mode Decomposition and Deep Convolution Neural Network by Shude Cai, Chunhua Fang, Yongyu Guo, Jialiang Liu, Gu Zhou

“…As a relatively weak part of cable insulation, T-type cable terminals will have insulation defects due to process, installation, and other problems, resulting in partial discharge. Therefore, this paper uses Deep Convolution Neural Network (DCNN) and Empirical Mode Decomposition (EMD) to identify the partial discharge type of a 10 kV T-type cable terminal. …”
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Convolution Representation of Traveling Pulses in Reaction-Diffusion Systems by Satoshi Kawaguchi

“…Convolution representation manifests itself as an important tool in the reduction of partial differential equations. …”
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Target Tracking via Particle Filter and Convolutional Network by Hongxia Chu, Kejun Wang, Xianglei Xing

“…Predefined convolutional filters are used to extract the high-order features. …”
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