AFQSeg: An Adaptive Feature Quantization Network for Instance-Level Surface Crack Segmentation by Shaoliang Fang, Lu Lu, Zhu Lin, Zhanyu Yang, Shaosheng Wang

“…However, under real-world conditions such as poor image quality, environmental interference, and complex crack patterns, existing models still face challenges in detecting fine cracks and often rely on large training parameters, limiting their practicality in complex environments. To address these issues, this paper proposes a crack detection model based on adaptive feature quantization, which primarily consists of a maximum soft pooling module, an adaptive crack feature quantization module, and a trainable crack post-processing module. …”
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MPVF: Multi-Modal 3D Object Detection Algorithm with Pointwise and Voxelwise Fusion by Peicheng Shi, Wenchao Wu, Aixi Yang

“…The IR module uses a group convolution strategy to inject high-level semantic features into the PWF and VWF modules, improving extraction efficiency. …”
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Learning spatial‐frequency interaction for generalizable deepfake detection by Tianbo Zhai, Kaiyin Lu, Jiajun Li, Yukai Wang, Wenjie Zhang, Peipeng Yu, Zhihua Xia

“…The dual‐stream frequency‐spatial fusion network consists of three components: the spatial forgery feature extraction module, the frequency forgery feature extraction module, and the spatial–frequency feature fusion module. …”
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MPVT: An Efficient Multi-Modal Prompt Vision Tracker for Visual Target Tracking by Jianyu Xie, Yan Fu, Junlin Zhou, Tianxiang He, Xiaopeng Wang, Yuke Fang, Duanbing Chen

“…Three key components are involved in the model: a decoupled input enhancement module, a dynamic adaptive prompt fusion module, and a fully connected head network module. …”
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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

“…We introduce dynamic multiscale convolution attention module, which consists of multiscale context aggregation (MCA) module and dynamic partial convolution attention (DPCATT) module. …”
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Forest Fire Detection Algorithm Based on Improved YOLOv11n by Kangqian Zhou, Shuihai Jiang

“…First, the C3k2 module was redesigned using the FasterBlock module, replacing C3k2 with C3k2-Faster in both the Backbone network and Neck section to achieve a lightweight model design. …”
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Facial recognition targeted attack algorithm based on multiscale frequency decomposition and meta-learning by CAI Jun, HUANG Tianqiang, ZHENG Aokun, YE Feng, XU Chao

“…The meta-learning attack module addressed the overfitting and generalization issues present in previous white-box model ensemble attacks, thereby enhancing the efficacy and generalization ability of the generated adversarial examples. …”
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Road Obstacle Detection Method Based on Improved YOLOv5 by Pengliu Tan, Zhi Wang, Xin Chang

“…Second, the SPPF module is replaced with the C3SPPF module to improve the model’s understanding of contextual information and increase its multi-scale adaptability. …”
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Knowledge graph construction and talent competency prediction for human resource management by Bowen Yang, Zhixuan Shen

“…To address these challenges, we propose a hybrid model that integrates Graph Convolutional Networks (GCN), Reinforcement Learning (RL), and Deep Collaborative Filtering (DCF). The GCN module captures complex multi-relational structures between jobs and candidates, the RL module dynamically optimizes recommendation strategies based on feedback, and the DCF module enhances personalized recommendation capabilities. …”
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Research on key management and authentication protocol of PDA in smart grid by Xiao YU, Li TIAN, Zhe LIU, Jie WANG

“…According to PDA in smart grid,which faced with security issues,key management and authentication protocol for PDA in smart grid based on scrambling PUF were presented.With the construction of mobile trusted platform by trusted hardware module and PDA,a key management mechanism was designed which presented for the indentify of hardware and controlled by user,to guarantee the security of key management and build a safe and effective mechanism of key backup and recovery.Based on trusted hardware module,security access for PDA in smart grid was realized,with the public and private key of key management strategy and improved access authentication protocol based on public key cryptography.…”
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Bilateral enhancement network with signal-to-noise ratio fusion for lightweight generalizable low-light image enhancement by Junfeng Wang, Shenghui Huang, Zhanqiang Huo, Shan Zhao, Yingxu Qiao

“…To improve the network’s generalization ability, we propose a Luminance Normalization (LNM) module for preprocessing and a Dual-Exposure Processing (DEP) module for post-processing. …”
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Retinex-Net mine image enhancement algorithm based on adaptive illumination estimation by Feng TIAN, Tingting CHEN, Xiaopei LIU

“…In the reflection component processing, an attention module CBAM (Convolutional Block Attention Module) is introduced to enhance the details and contrast of the image, thereby improving clarity. …”
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Research on an adaptive multimodal cognitive load classification method by Xiangxin Yu, Ruizhen Wang

“…Methods: To address these issues, this study proposes a cognitive load classification algorithm based on Multimodal Domain Adaptation (MMDA), which comprises an Intra-Modal Domain Adaptation (IMDA) module and a Cross-Modal Domain Adaptation (CMDA) module. …”
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Le paysage pour aborder les interactions entre environnement alpin et sociétés by Sylvie Paradis, Stéphanie Girardclos, Cédric Lambert, Mathieu Petite, Marjorie Perroud

“…In the autumn of 2015, a module entitled “Landscape Issues” (in French, “Enjeux paysagers”) was introduced in the first semester of the University Master of Environmental Sciences (in French, Master Universitaire en Sciences de l’Environnement, MUSE), an interdisciplinary and interfaculty training course at Geneva University (Switzerland). …”
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Detection method for dangerous behaviors of underground coal mine personnel by ZHANG Xuhui, YU Henghan, DU Yuyang, YANG Wenjuan, ZHAO Yihui, WAN Jicheng, WANG Yanqun, ZHAO Dian, TANG Duwei

“…The standard convolution was replaced with a hybrid DCNv4-PConv module, which combines the DCNv4 network and the deformable capability of the PConv module. …”
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Multi-scale sparse convolution and point convolution adaptive fusion point cloud semantic segmentation method by Yuxuan Bi, Peng Liu, Tianyi Zhang, Jialin Shi, Caixia Wang

“…Second, to mitigate significant differences between single-type and single-scale features, we propose a multi-scale feature fusion cross-gating module. This module employs gating mechanisms to improve fusion accuracy between different scale receptive fields. …”
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MFAFNet: Multi-Scale Feature Adaptive Fusion Network Based on DeepLab V3+ for Cloud and Cloud Shadow Segmentation by Yijia Feng, Zhiyong Fan, Ying Yan, Zhengdong Jiang, Shuai Zhang

“…Second, a Global Context Attention Module (GCAM) is incorporated into the Atrous Spatial Pyramid Pooling (ASPP) module to establish pixel-wise long-range dependencies, thereby effectively integrating global semantic information. …”
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An unsupervised underwater image enhancement method based on generative adversarial networks with edge extraction by Yanfei Jia, Ziyang Wang, Liquan Zhao

“…Second, we propose an edge extraction block based on the Laplacian operator, an attention module with an edge extraction block, a multi-scale feature module, a novel upsampling module, and a new downsampling module. …”
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EBBA-detector: An effective detector for defect detection in solar panel EL images with unbalanced data. by Yixing Zhang, Ziyan Mo, Zhuan Xin, Xianyu Chen, Yuqin Deng, Xuan Dong

“…Solar panel defect detection, a crucial quality control task in the manufacturing process, often faces challenges such as varying defect sizes, severe image background interference, and imbalanced data sample distribution. To address these issues, this paper proposes the EBBA-Detector. The core of the model lies in an enhanced balanced attention framework, which includes an Enhanced Bidirectional Feature Pyramid Network (EBFPN) and a Balanced-Attention Module (B-A Module). …”
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Design for manufacture and assembly (DfMA) for modular buildings: an analytical framework by Vikrom Laovisutthichai, Wilson Lu

“…Several design patterns are also identified, i.e. typical space requirements, common module sizes, dimension-coordinated spaces, and the repetitive use of standardized spaces and modules to form units. …”
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