Research on the Method of Crop Pest and Disease Recognition Based on the Improved YOLOv7-U-Net Combined Network by Wenchao Xiang, Zitao Du, Xinran Liu, Zehui Lu, Yuna Yin

“…This paper proposes an improved YOLOv7-U-Net combined network for crop pest and disease recognition, aiming to address the issue of insufficient accuracy in existing methods. …”
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A brain tumor segmentation method based on attention mechanism by Juan Cao, Jinjia Liu, Jiaran Chen

“…Additionally, a spatial attention module (SPA) is introduced to establish global feature correlations, critical for accurate tumor segmentation. …”
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A Pump‐Free, Hydraulic‐Amplification Oscillatory Microfluidic Device for Continuous Particle and Cell Manipulation by Yong Liu, Mingyi Liang, Shanshan Xu, Sheng Yan

“…The PHOMF device has a hydraulic‐amplification module for pressure transfer and a soft microchannel module for the generation of oscillatory flows. …”
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Knowledge graph convolutional networks with user preferences for course recommendation by Zhong Hua, Jianbai Yang, Weidong Ji

“…The KGCN-UP model consists of two key modules. First, the user preference propagation module refines user preferences by exploring relational chains in the knowledge graph and dynamically adjusting attention to improve user representation. …”
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PRNet: 3D Object Detection Network-Based on Point-Region Fusion by Yufei Fu, Yuhao Guo, Hui Hu

“…The designed Image Feature Fusion module (IF-Fusion) fuses image feature maps of varying sizes in a pairwise manner. …”
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MSCSCC-Net: multi-scale contextual spatial-channel correlation network for forgery detection and localization of JPEG-compressed image by Wuyang Shan, Jingchuan Yue, Steven X. Ding, Junying Qiu

“…We design a contextual spatial correlation module (CSCM) and a contextual channel correlation module (CCCM) to generate contextual spatial-channel features at different scales, with the aim of distinguishing between JPEG artifacts, forgery artifacts, and authentic regions. …”
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CME Arrival Time Prediction via Fusion of Physical Parameters and Image Features by Yufeng Zhong, Dong Zhao, Xin Huang, Long Xu

“…First, we design a parameter feature extraction module that extracts features from CME physical parameters. …”
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CPCROK: A Communication-Efficient and Privacy-Preserving Scheme for Low-Density Vehicular Ad Hoc Networks by Junchao Wang, Honglin Li, Yan Sun, Chris Phillips, Alexios Mylonas, Dimitris Gritzalis

“…Specifically, the CPCROK consists of three main modules: firstly, a special Kalman filter module that provides real-time, coarse-grained vehicle trajectory estimates to reduce the need for real-time vehicle state information; secondly, a Recurrent Neural Network (RNN) module that enhances predictions within the mix zone by incorporating offline data engineering and considering online vehicle steering angles; and finally, a trajectory generation module that collaborates with the first two to generate highly convincing fake trajectories outside the mix zone. …”
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Design of an Electronic Nose System with Automatic End-Tidal Breath Gas Collection for Enhanced Breath Detection Performance by Dongfu Xu, Pu Liu, Xiangming Meng, Yizhou Chen, Lei Du, Yan Zhang, Lixin Qiao, Wei Zhang, Jiale Kuang, Jingjing Liu

“…Therefore, accurate collection of end-tidal breath gases is crucial to enhance electronic noses’ performance in breath detection. Regarding this issue, this study proposes a novel electronic nose system and employs a threshold control method based on exhaled gas flow characteristics to design a gas collection module. …”
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Infrared Aircraft Detection Algorithm Based on High-Resolution Feature-Enhanced Semantic Segmentation Network by Gang Liu, Jiangtao Xi, Chao Ma, Huixiang Chen

“…Secondly, based on the idea of using dilated convolutions to expand the receptive field of feature maps, a hybrid atrous spatial pyramid pooling module is designed. By utilizing a serial structure of dilated convolutions with small dilation rates, this module addresses the issue of feature information loss when expanding the receptive field through dilated spatial pyramid pooling. …”
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Synergistic Semantic Segmentation and Height Estimation for Monocular Remote Sensing Images via Cross-Task Interaction by Xuanang Peng, Shixin Wang, Futao Wang, Jinfeng Zhu, Suju Li, Longfei Liu, Zhenqing Wang

“…Finally, we propose a task feature interaction module to optimize features across tasks through mutual optimization, maximizing task-specific feature expression. …”
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Cotton Leaf Disease Detection Using LLM-Synthetic Data and DEMM-YOLO Model by Lijun Gao, Tiantian Ran, Hua Zou, Huanhuan Wu

“…To tackle the challenges of large-scale variations and irregular lesion distribution, we design a multi-scale feature aggregation module (MFAM). This module integrates multi-scale semantic information through a lightweight, multi-branch convolutional structure, enhancing the model’s ability to detect small-scale lesions. …”
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Image dehazing algorithm based on light-value weighted allocation and multi-layer restricted perception by Dongyang Shi, Sheng Huang, Wei Zhao

“…We propose an image dehazing algorithm based on light-value weighted allocation and multi-layer restricted perception (DWARP) to address these issues. The proposed algorithm first constructs an atmospheric light estimation module based on weighted allocation. …”
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Target Detection Method for Soil-Dwelling Termite Damage Based on MCD-YOLOv8 by Peidong Jiang, Lai Jiang, Fengyan Wu, Tengteng Che, Ming Wang, Chuandong Zheng

“…This study developed an improved YOLOv8 model, named MCD-YOLOv8, for identifying traces of soil-dwelling termite activity, based on the Monte Carlo random sampling algorithm and a lightweight module. The Monte Carlo attention (MCA) module was introduced in the backbone part to generate attention maps through random sampling pooling operations, addressing cross-scale issues and improving the recognition accuracy of small targets. …”
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Cascade DeepLab Net: A Method for Accurate Extraction of Fragmented Cultivated Land in Mountainous Areas Based on a Cascaded Network by Man Li, Renru Wang, Ana Dai, Weitao Yuan, Guangbin Yang, Lijun Xie, Weili Zhao, Linglin Zhao

“…This model enhances the accuracy of cultivated land extraction in complex terrains by incorporating the Style-based Recalibration Module (SRM), Spatial Attention Module (SAM), and Refinement Module (RM). …”
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MFCEN: A lightweight multi-scale feature cooperative enhancement network for single-image super-resolution by Jiange Liu, Yu Chen, Xin Dai, Li Cao, Qingwu Li

“…The network introduced a novel comprehensive integrated multi-level feature module, leveraging the strong local perceptual capabilities of CNNs and the superior global information processing of transformers. …”
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Research on Method in Measurement and Parameter of Energy Saving for WLAN Access Point by Bo Gao, Fei Wu, Rui Lin, Chengbin Shen

“…As the fast growing of WLAN's access point（AP）, reducing power consumption of large amount of AP became an important issue in telecommunication industry. Many similar products test methods and standards in power consumption area which proposed by different nations and organizations were referred. …”
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Vision-Transformer Model Validation Image Dataset by Mathew G. Pelletier, John D. Wanjura, Greg A. Holt

“…The removal of plastic contamination from cotton lint is a critical issue for the U.S. cotton industry. One primary source of this contamination is the plastic wrap used on cotton modules by John Deere round module harvesters. …”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…A Global Attention Module (GAM) is integrated to improve the model's perception of global information. …”
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LPFFNet: Lightweight Prior Feature Fusion Network for SAR Ship Detection by Xiaozhen Ren, Peiyuan Zhou, Xiaqiong Fan, Chengguo Feng, Peng Li

“…A perception lightweight backbone network (PLBNet) is designed to reduce model complexity, and a multi-channel feature enhancement module (MFEM) is introduced to enhance the SAR ship localization capability. …”
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