Detection of water surface targets based on improved Deformable DETR by Pengjiu WANG, Junbin Gong, Wei LUO, Xiao HUANG, Junjie GUO

“…The experimental results on different datasets verify the effectiveness of the algorithm. …”
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Automatic segmentation and quantitative analysis of brain CT volume in 2-year-olds using deep learning model by Fengjun Xi, Liyun Tu, Feng Zhou, Yanjie Zhou, Jun Ma, Yun Peng

“…In addition, we compared the performance of the ResU-Net model with different kernel sizes (3 × 3 × 3 and 1 × 3 × 3 convolution kernels) against the baseline model, which was the standard 3D U-Net. …”
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DCP-YOLOv7x: improved pest detection method for low-quality cotton image by Yukun Ma, Yajun Wei, Minsheng Ma, Zhilong Ning, Minghui Qiao, Uchechukwu Awada

“…In addition, the model detection head part is replaced with a DyHead (Dynamic Head) structure, which dynamically fuses the features at different scales by introducing dynamic convolution and multi-head attention mechanism to enhance the model's ability to cope with the problem of target morphology and location variability.ResultsThe model was fine-tuned and tested on the Exdark and Dk-CottonInsect datasets. …”
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A Method to Improve Computational Efficiency of Productivity Evaluation with Rectangular Coalbed Methane Reservoir by Li Chen, Sun Lichun, Sun Hansen, Feng Ruyong, Wang Cunwu, Zhang Fang

“…It is clarified that its impacts are different in the early stage and the later stage of production. …”
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Modeling Marine Geoid in the China Seas and Its Adjacent Ocean Based on Satellite Altimeter-Derived Gravity Anomaly Model by Huiying Zhang, Xin Liu, Zhen Li, Xiaotao Chang, Heping Sun, Hui Li, Jinyun Guo

“…Compared with the mean dynamic topography of DTU22MDT, the difference between the two mean dynamic topography was basically within the range of centimeters. …”
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ETUDE DE LA REFLEXION DE L’ONDE ULTRASONORE DANS LE DOMAINE TEMPOREL by Kahina LOUANI

“…En application, on a choisi différents signaux d’entrée puis, par convolution numérique, on retrouve la forme du signal correspondant à l’onde réfléchie. …”
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Using deep learning for detecting BotCloud by Guang KOU, Guang-ming TANG, Shuo WANG, Hai-tao SONG, Yuan BIAN

“…The differences of the basic network flow characteristics between BotCloud and normal cloud services were not obvious, and this led to the inefficiency of the method in BotCloud detection based on network flow characteristics analysis. …”
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AI-enhanced patient-specific dosimetry in I-131 planar imaging with a single oblique view by Mostafa Jalilifar, Mahdi Sadeghi, Alireza Emami-Ardekani, Ahmad Bitarafan-Rajabi, Kouhyar Geravand, Parham Geramifar

“…Notably, MLP-based dose estimations closely matched ground truth data with < 15% differences in most tissues. The MLP-estimated dose values present a robust patient-specific dosimetry approach capable of swiftly predicting absorbed doses in different organs using WB planar images and a single oblique view. …”
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DGCFNet: Dual Global Context Fusion Network for remote sensing image semantic segmentation by Yuan Liao, Tongchi Zhou, Lu Li, Jinming Li, Jiuhao Shen, Askar Hamdulla

“…The semantic segmentation task of remote sensing images often faces various challenges such as complex backgrounds, high inter-class similarity, and significant differences in intra-class visual attributes. Therefore, segmentation models need to capture both rich local information and long-distance contextual information to overcome these challenges. …”
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Transmission Line Anomaly Detection and Real-Time Monitoring System Combining Edge Computing and EfficientDet by Menghao Lin, Yang Ding, Tianle Wang, Yang Liu, Zewei Li

“…The experimental results show that the proposed method effectively improves recognition accuracy and recall rate, achieving over 88% on different types of transmission lines. The ablation experiment shows that adding K-means clustering algorithm and gradient equalization mechanism can significantly improve recognition accuracy.…”
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Visible-infrared person re-identification with region-based augmentation and cross modality attention by Yuwei Guo, Wenhao Zhang, Licheng Jiao, Shuang Wang, Shuo Wang, Fang Liu

“…Specifically, we propose a region-based data augmentation module PedMix to enhance pedestrian region coherence by mixing the corresponding regions from different modalities, thus generating more natural images. …”
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Position-Aware Graph Neural Network for Few-Shot SAR Target Classification by Jia Zheng, Ming Li, Peng Zhang, Yan Wu, Hongmeng Chen

“…Synthetic aperture radar (SAR) target classification methods based on convolutional neural networks (CNNs) are susceptible to overfitting due to limited samples. …”
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Identification of Low‐Value Defects in Infrared Images of Porcelain Insulators Based on STCE‐YOLO Algorithm by Shaotong Pei, Weiqi Wang, Chenlong Hu, Keyu Li, Haichao Sun, Mianxiao Wu, Bo Lan

“…And the multiple attention mechanism improved to the third generation of variability convolution is used to detect the head to improve the accuracy of the algorithm's target localization. …”
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Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…Additionally, a channel attention network is integrated to establish channel interconnections, expanding the receptive field and enhancing the extraction of finegrained features at different scales, thereby improving the detection capability for targets of various sizes, especially small targets. …”
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A Sparse Feature-Based Mixed Signal Frequencies Detecting for Unmanned Aerial Vehicle Communications by Yang Wang, Yongxin Feng, Fan Zhou, Xi Chen, Jian Wang, Peiying Zhang

“…On this basis, complex dilated convolution and deconvolution are used successively to perform feature extraction on the separated signals, which enhances the receptive field and frequency resolution ability of the network for signals, reduces the interference between noise and different component signals, and realizes the accurate estimation of the number of components and carrier frequencies. …”
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A Multi-Scale Adaptive Fusion Network: End-to-End Interpretable Small-Sample Classifier for Motor Imagery EEG by Qiulei Han, Yan Sun, Ze Song, Hongbiao Ye, Tingwei Chen, Jian Zhao

“…The SCA module strengthens the model&#x2019;s ability to perceive features of different frequencies and spatio-temporal information through multi-scale feature interactions to extract richer primary feature representations. …”
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A High-Precision Defect Detection Approach Based on BiFDRep-YOLOv8n for Small Target Defects in Photovoltaic Modules by Yi Lu, Chunsong Du, Xu Li, Shaowei Liang, Qian Zhang, Zhenghui Zhao

“…Secondly, for the multi-scale characteristics of defects, the neck network is optimized by introducing a bidirectional weighted feature pyramid network (BiFPN), which adopts an adaptive weight allocation strategy to enhance feature fusion and improve the characterization of defects at different scales. Finally, the detection head part uses DyHead-DCNv3, which combines the triple attention mechanism of scale, space, and task awareness, and introduces deformable convolution (DCNv3) to improve the modeling capability and detection accuracy of irregular defects.…”
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PFARN: Pyramid Fusion Attention and Refinement Network for Multiscale Ship Detection in SAR Images by Ke Li, Hang Yu, Suqi Li, Shanhu Chen, Bailu Wang

“…However, different from optical images, the SAR images have their own unique characteristics, posing challenges to the direct application of CNNs. …”
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Nondestructive freshness recognition of chicken breast meat based on deep learning by Rui Jian, Guangbo Li, Xie Jun, Guolong Shi

“…Specifically, chicken breast samples under different lighting intensities, densities, sampling angles, etc., were collected. …”
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SR-YOLO: Spatial-to-Depth Enhanced Multi-Scale Attention Network for Small Target Detection in UAV Aerial Imagery by Shasha Zhao, He Chen, Di Zhang, Yiyao Tao, Xiangnan Feng, Dengyin Zhang

“…First, the Space-to-Depth layer and Receptive Field Attention Convolution are combined, and the SR-Conv module is designed to replace the Conv module within the original backbone network. …”
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