Efficient detection of highway pavement cracks using computer vision-based MSFNet model by Zhengfa Jiang, Danlan Li, Ting Zhao, Mingxing Gao

“…It uses blueprint separable convolution(BSConv) and MobileViT block to build a lightweight local and global crack feature extraction network, and incorporates a Self-Focus module to avoid feature information loss; Furthermore, to automatically correct the restoration of feature maps at different levels, we design a multilevel correction decoder(MCD) based on the coordinate-aware fusion(CAF) module; Then, combine it with a linear feature refining head to make the network's receptive field more consistent with the crack distribution in real scenarios. …”
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A Self-Supervised Monocular Depth Estimation Framework Based on Detail Recovery and Feature Fusion by Shun Li, Chongzheng Huang, Xiangzhe Li, Zhengyou Liang

“…MDAFM captures feature information from different perspectives and levels to address the problem of critical information loss, while HPCB effectively captures and fuses local and global information through parallel processing. …”
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Quantitative analysis of the nephron during human fetal kidney development by Daković-Bjelaković Marija Z., Vlajković Slobodan R., Čukuranović Rade E., Antić Svetlana, Bjelaković Goran B., Mitić Dejan

“…Glomeruli changed their size and shape, while the tubules changed their length and convolution. Renal cortex became wider and contained the more mature glomeruli and the more convoluted tubules. …”
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Adaptive Threshold Algorithm for Outlier Elimination in 3D Topography Data of Metal Additive Manufactured Surfaces Obtained from Focus Variation Microscopy by Xin Xu, Tobias Pahl, Sebastian Hagemeier, Peter Lehmann

“…This paper introduces a method for deriving self-adaptive thresholds from the convolution result and compares the effects of different operators in creating self-adaptive thresholds. …”
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Underwater Time Delay Estimation Based on Meta-DnCNN with Frequency-Sliding Generalized Cross-Correlation by Meiqi Ji, Xuerong Cui, Juan Li, Lei Li, Bin Jiang

“…Firstly, a multi-sub-window reconstruction is performed on the frequency-sliding generalized colorboxpinkcross-correlation (FS-GCC) matrix between signals to capture the time delay characteristics from different frequency bands and conduct the enhancement and extraction of features. …”
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Refined Anchor-Free Model With Feature Enhancement Mechanism for Ship Detection in Infrared Images by Yunlong Gao, Chuan Wu, Ming Ren, Yang Feng

“…Secondly, a multiattention fusion module based on convolution kernels with different sizes is embedded into the backbone to distinguish the spatial salience of the targets from the complex surroundings. …”
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Real-Time Wave Energy Converter Control Using Instantaneous Frequency by Inyong Kim, Ted K. A. Brekken, Solomon Yim, Brian Johnson, Yue Cao, Pranav Chandran

“…Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. …”
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Polarization of road target detection under complex weather conditions by Feng Huang, Junlong Zheng, Xiancai Liu, Ying Shen, Jinsheng Chen

“…A multi-scale detection network is also designed to fully extract and fuse multi-scale feature information from receptive fields, channels, and spaces in different dimensions. Additionally, a dataset of Polarized Images of Road Targets in Complex Weather conditions (PIRT-CW) is proposed for training and evaluation. …”
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Early stroke behavior detection based on improved video masked autoencoders for potential patients by Meng Wang, Guanci Yang, Kexin Luo, Yang Li, Ling He

“…After that, the optimal parameters of EPBR-PS were determined through the experiment of learning rate and fusion weights of different features. On the NTU-ST dataset, comparative analysis with eight models demonstrated the superiority of EPBR-PS, evidenced by the average recognition accuracy of 89.61%, surpassing that 1.67% over the benchmark VideoMAE. …”
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GrotUNet: a novel leaf segmentation method by Hongfei Deng, Hongfei Deng, Bin Wen, Bin Wen, Cheng Gu, Yingjie Fan

“…Unlike UNet++ dense connectivity, jump connection reconstruction only uses 1×1  convolution for feature fusion of feature maps from different network hierarchies to enrich the semantic information at each location in the space. …”
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Physiological signal-based mental stress detection using hybrid deep learning models by Nandini Modi, Yogesh Kumar, Kapil Mehta, Neelam Chaplot

“…The dataset comprises a diverse set of physiological biomarkers correlated with different mental states. The algorithm begins by segmenting preprocessed EEG data and extracting time–frequency features using Short-Time Fourier Transform (STFT). …”
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Feature Fusion to Improve YOLOv8 for Segmenting and Classifying Aerial Images of Tree Crowns by Ziyi Sun, Bing Xue, Mengjie Zhang, Jan Schindler

“…Moreover, YOLOv8-FF incorporates a FF mechanism that includes both cross-scale and same-scale fusion methods, enhancing the model’s ability to integrate information across different layers and scales, thereby improving segmentation performance. …”
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Interaction-Temporal GCN: A Hybrid Deep Framework For Covid-19 Pandemic Analysis by Zehua Yu, Xianwei Zheng, Zhulun Yang, Bowen Lu, Xutao Li, Maxian Fu

“…Therefore, we propose a novel framework, the Interaction-Temporal Graph Convolution Network (IT-GCN), to analyze pandemic data. …”
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Cross-Domain Person Re-Identification Based on Multi-Branch Pose-Guided Occlusion Generation by Pengnan Liu, Yanchen Wang, Yunlong Li, Deqiang Cheng, Feixiang Xu

“…Secondly, a multi-branch feature fusion structure is constructed. By fusing different feature information from the global and occlusion branches, the diversity of features is enriched. …”
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Non-Destructive Detection Method of Apple Watercore: Optimization Using Optical Property Parameter Inversion and MobileNetV3 by Zihan Chen, Haoyun Wang, Jufei Wang, Huanliang Xu, Ni Mei, Sixu Zhang

“…To determine whether different batches of apples are suitable for long-term storage or long-distance transportation, and to classify the apples according to quality level to enhance the economic benefits of the apple industry, it is essential to conduct non-destructive testing for watercore. …”
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MMI Couplers and the Talbot Effect, Symmetries and Golden Ratio by Gazi Mahamud Hasan, Mehedi Hasan, Karin Hinzer, Trevor Hall

“…The position of the anti-symmetry axis controls the distribution of discrete lattice points in a unit cell. For different distributions, interesting features such as conditional flexibility in the placement of access ports without altering amplitude and phase relationships, omitting ports without power penalty, closed form uneven splitting ratios, and offset access ports can be derived from the MMI coupler. …”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…An attention-guided network (AGNet) is a network that utilizes attention to guide information across different scales. Its feature extraction module employs a dual-branch information residual unit (DIRU) as a substitute for the conventional convolution block, which combines the feature extraction capabilities of global pooling and max pooling, reducing the number of parameters while also achieving a certain improvement in detection results. …”
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Neural Networks Detection of Low-Amplitude Components on ECG Using Modified Wavelet Transform by A. V. Mnevets, N. G. Ivanushkina

“… This study is devoted to identification of low amplitude components from ECG signals by different time-frequency analysis methods when main power spectrum falls on high-amplitude components. …”
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Retinal vascular segmentation network based on dual-scale morphological enhancement by Yunfeng Ni, Pei Wang, Wei Chen, Jie Qi

“…Subsequently, a feature aggregation module based on dynamic snake-shaped convolutions is introduced, which adapts convolution paths to achieve the fusion of features at different levels. …”
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SECrackSeg: A High-Accuracy Crack Segmentation Network Based on Proposed UNet with SAM2 S-Adapter and Edge-Aware Attention by Xiyin Chen, Yonghua Shi, Junjie Pang

“…This function also applies Multi-Granularity Supervision by optimizing segmentation outputs at three different resolution levels, ensuring better feature consistency and improved model robustness across varying image scales. …”
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