A weakly-supervised follicle segmentation method in ultrasound images by Guanyu Liu, Weihong Huang, Yanping Li, Qiong Zhang, Jing Fu, Hongying Tang, Jia Huang, Zhongteng Zhang, Lei Zhang, Yu Wang, Jianzhong Hu

“…We propose the Weakly Supervised Follicle Segmentation (WSFS) method, a novel one-stage weakly supervised segmentation technique model designed to enhance the ultrasound images of follicles, which incorporates a Convolutional Neural Network (CNN) backbone augmented with a Feature Pyramid Network (FPN) module for multi-scale feature representation, critical for capturing the diverse sizes and shapes of follicles. …”
Get full text

ECAN-Detector: An Efficient Context-Aggregation Network for Small-Object Detection by Gaofeng Xing, Zhikang Xu, Yulong He, Hailong Ning, Menghao Sun, Chunmei Wang

“…Concurrently, a context-augmentation module (CAM) embedded in the shallow layer complements both global and local features relevant to small objects. …”
Get full text

Channel attention pyramid network for remote physiological measurement by Jing Zhang, Haixin Sun, Yuhao Hu, Guanghao Zhu, Fang Liu, Boyun Yan, Jiahao Pu, Xiaohui Du, Juanxiu Liu, Lin Liu, Ruqian Hao, Xingguo Wang, Yong Liu

“…This method employs a multi-scale deep learning architecture with a Gaussian pyramid to capture facial features at different scales that are often overlooked in prior work. A channel attention module further emphasizes rPPG-rich channels, mitigating the issue of feature dilution caused by excessive channel depth and enhancing the accuracy of physiological signal extraction from facial videos. …”
Get full text

Post-approval variations to dossiers for vaccines: analysis of regulatory and methodological approaches used in the Russian Federation and abroad by V. A. Shevtsov, Yu. V. Olefir, V. A. Merkulov, V. P. Bondarev, I. N. Indikova, E. E. Evreinova, A. V. Rukavishnikov, L. M. Khantimirova, D. V. Gorenkov

“…Competent authorities that use the module format of the registration dossier, i.e. the regulatory authorities of the European Union, USA and other members of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH), and the Eurasian Economic Union (EEU), issue guidelines on changes to registration dossiers for pharmaceuticals and biologicals (immunological products). …”
Get full text

Beyond Hunger: Uncovering the Link between Food Insecurity and Depression, Anxiety, and Stress in Adolescents by Emily Cisneros-Vásquez, Lee Smith, Rodrigo Yañéz-Sepúlveda, Jorge Olivares-Arancibia, Héctor Gutiérrez-Espinoza, Dong Keon Yon, Jae Il Shin, José Francisco López-Gil

“…FI was assessed via the Child Food Security Survey Module, whereas mental health symptoms were evaluated via the Depression, Anxiety, and Stress Scale. …”
Get full text

Physical violence and its associations: Insights from nationally representative data in India by Monisha Mary P, Ankeeta Menona Jacob, Avinash K Shetty

“…Methods: Data from NFHS-5, focusing on women aged 15–49 who completed the domestic violence module, were analyzed. Women’s empowerment was measured through employment, asset ownership, and decision-making autonomy. …”
Get full text

ETV-MVS: Robust Visibility-Aware Multi-View Stereo with Epipolar Line-Based Transformer by Shaoqian Wang, Xiaokun Ding, Yuxin Mao, Yuchao Dai

“…In this paper, we propose an innovative visibility-aware framework to address these issues. Central to our method is an Epipolar Line-based Transformer (ELT) module, which capitalizes on the epipolar line correspondence and candidate matching features between images to enhance the feature representation and correlation robustness. …”
Get full text

Manhattan Correlation Attention Network for Metal Part Anomaly Classification by Zijiao Sun, Yanghui Li, Fang Luo, Zhiliang Zhang, Jiaqi Huang, Qiming Zhang

“…However, it is difficult to detect metal anomalies due to the following issues: 1) Some defects of metal parts areas are small; 2) The abnormal metal regions are relatively similar to the normal ones. …”
Get full text

Detection method of potato leaf disease based on YOLOv5s by Jingtao Li, Hao Chen, Guisong Li, Yueqi Liu, Yanli Yang, Xia Liu, Chang Yi Wang

“… An improved leaf target detection method based on the YOLOv5s network is proposed to address the issues of low model detection accuracy and slow detection speed in potato leaf image target detection. …”
Get full text

Online evaluation method for MMC submodule capacitor aging based on CapAgingNet by Xinlan Deng, Youhan Deng, Liang Qin, Weiwei Yao, Min He, Kaipei Liu

“…Subsequently, the CapAgingNet model is introduced, incorporating key technical modules to enhance performance: the Deep Stem module, which extracts larger receptive fields through multiple convolution layers and mitigates the impact of data sparsity in capacitor aging on feature extraction; the efficient channel attention (ECA) module, utilizing one-dimensional convolution for dynamic weighting to adjust the importance of each channel, thereby enhancing the ability of the model to process high-dimensional features in capacitor aging data; and the multiscale feature fusion (MSF) module, which integrates capacitor aging information across different scales by combining fine-grained and coarse-grained features, thus improving the capacity of the model to capture high-frequency variation characteristics. …”
Get full text

Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

“…We designed a new module that optimises the computational complexity of networks and fused the module with the attention mechanism SimAM to solve the problem of low efficiency in detecting flashover faults. …”
Get full text

HGNN-GAMS: Heterogeneous Graph Neural Networks for Graph Attribute Mining and Semantic Fusion by Yufei Zhao, Hua Liu, Hua Duan

“…The semantic aggregation module, leveraging an attention mechanism, integrates diverse semantic information within HGs. …”
Get full text

Face Anti-Spoofing Based on Adaptive Channel Enhancement and Intra-Class Constraint by Ye Li, Wenzhe Sun, Zuhe Li, Xiang Guo

“…The ECA module extracts features through deep convolution, while the Bottleneck Reconstruction Module (BRM) employs a channel compression–expansion mechanism to refine spatial feature selection. …”
Get full text

An Improved YOLOv7-Tiny-Based Algorithm for Wafer Surface Defect Detection by Mengyun Li, Xueying Wang, Hongtao Zhang, Xiaofeng Hu

“…First, a coordinate attention (CA) module is incorporated into the feature extraction network to enhance the network’s ability to learn features at defect locations. …”
Get full text

Feature-Separated Lightweight Model for Road Extraction in Wild Environments by Che Shi, Yuefeng Cen, Gang Cen

“…A Feature Separation and Enhancement Module (FSEM) independently processes spatial and channel features, while a Feature Aggregation Module (FAM) integrates multi-scale features for improved road continuity and accuracy. …”
Get full text

Denoising and Feature Enhancement Network for Target Detection Based on SAR Images by Cheng Yang, Chengyu Li, Yongfeng Zhu

“…First, we design a background suppression and target enhancement module (BSTEM), which aims to suppress noise interference in complex backgrounds. …”
Get full text

Improved YOLOv8n based helmet wearing inspection method by Xinying Chen, Zhisheng Jiao, Yuefan Liu

“…The YOLOv8 C2f module is enhanced with a new SC_Bottleneck structure, incorporating the SCConv module, now termed SC_C2f, to mitigate model complexity and computational costs. …”
Get full text

Underwater Image Enhancement Methods Using Biovision and Type-II Fuzzy Set by Yuliang Chi, Chao Zhang

“…In contrast, the method proposed in this paper applies a color correction module that takes into account the effects of biological vision in LAB color space, and an enhanced Type-II Fuzzy set visibility enhancement module. …”
Get full text

STBNA-YOLOv5: An Improved YOLOv5 Network for Weed Detection in Rapeseed Field by Tao Tao, Xinhua Wei

“…The ideal method for applying herbicides would be selective variable spraying, but the primary challenge lies in automatically identifying weeds. To address the issues of dense weed identification, frequent occlusion, and varying weed sizes in rapeseed fields, this paper introduces a STBNA-YOLOv5 weed detection model and proposes three enhanced algorithms: incorporating a Swin Transformer encoder block to bolster feature extraction capabilities, utilizing a BiFPN structure coupled with a NAM attention mechanism module to efficiently harness feature information, and incorporating an adaptive spatial fusion module to enhance recognition sensitivity. …”
Get full text

PoseNet++: A multi-scale and optimized feature extraction network for high-precision human pose estimation. by Chao Lv, Geyao Ma

“…Human pose estimation (HPE) has made significant progress with deep learning; however, it still faces challenges in handling occlusions, complex poses, and complex multi-person scenarios. To address these issues, we propose PoseNet++, a novel approach based on a 3-stacked hourglass architecture, incorporating three key innovations: the multi-scale spatial pyramid attention hourglass module (MSPAHM), coordinate-channel prior convolutional attention (C-CPCA), and the PinSK Bottleneck Residual Module (PBRM). …”
Get full text