Para-YOLO: An Efficient High-Parameter Low-Computation Algorithm Based on YOLO11n for Remote Sensing Object Detection by Hang Chen, Qi Cao, Yongqiang Wang, Shang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…By utilizing the intermediate layer of the feature fusion network as the aggregation-diffusion layer, it mitigates the feature degradation caused by consecutive upsampling in Feature Pyramid Networks. …”
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An enhanced network for extracting tunnel lining defects using transformer encoder and aggregate decoder by Bo Guo, Zhihai Huang, Haitao Luo, Perpetual Hope Akwensi, Ruisheng Wang, Bo Huang, Tsz Nam Chan

“…In the decoder, multi-scale information is initially aggregated using a Multi-Layer Perceptron (MLP) module. …”
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LEM-Detector: An Efficient Detector for Photovoltaic Panel Defect Detection by Xinwen Zhou, Xiang Li, Wenfu Huang, Ran Wei

“…To handle defects of varying scales, complementary semantic information from different feature layers is leveraged for enhanced feature fusion. A Multi-Scale Multi-Feature Pyramid Network (MMFPN) is employed to selectively aggregate boundary and category information, thereby improving the accuracy of multi-scale target recognition. …”
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Agriculture Sensor-Cloud Infrastructure and Routing Protocol in the Physical Sensor Network Layer by Kyuhyung Kim, Sungwon Lee, Hongseok Yoo, Dongkyun Kim

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Enhanced Lightweight YOLO Model for Efficient Vehicle Detection in Satellite Imagery by Mohamad Haniff Junos, Anis Salwa Mohd Khairuddin, Elmi Abu Bakar, Ahmad Faizul Hawary

“…Additionally, an improved small efficient layer aggregation network is adopted in the modified path aggregation network to enhance feature extraction across various scales. …”
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End-to-end multipath transport layer architecture oriented the next generation network by XUE Miao, GAO De-yun, ZHANG Si-dong, ZHANG Hong-ke

“…To solve the problem of inefficient transmission using multiple interfaces of multihome terminal in the tradition network,an end-to-end multipath transport layer architecture—E2EMP oriented the next generation network was presented.Through distributing data adaptively following characters of the end-to-end paths,adopting dual sequence space,implementing smart path management policies,the performance of the multihome terminal using E2EMP has significant improvement.The simulation results show that E2EMP aggregates bandwidth of the multihome terminal interfaces efficiently,and meanwhile promotes the security and reliability of end-to-end multipath transport.…”
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Edge-guided slicing and inference (EGSI) with feature aggregation network for quantification of large defective temporary construction materials by Njoroge James Mugo, Akbar Ali, Song Jinwoo, Soonwook Kwon

“…The proposed bottleneck layer in the feature aggregation network achieved a mean average precision (mAP) of 81.1%, outperforming the best custom model by 1.2%. …”
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MIDAS: A Data Aggregation Scheduling Scheme for Variable Aggregation Rate WSNs by Jun Long, An He, Jinhuan Zhang, Hao Zhang

“…Data aggregation scheduling for variable aggregation rate model has wide application and should take network lifetime and energy efficiency into consideration. …”
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Information exchange model of multi control nodes in trustworthy and controllable network by WANG Peng, LUO Jun-zhou, LI Wei, ZHENG Xiao, QU Yan-sheng

“…A new model based on two-layer Chord was proposed to realize information exchange between multi control nodes in trustworthy and controllable network.It constructs the two-layer Chord by constructing Chord between control nodes in AS and between ASes respectively.It uses this two-layer Chord to generate a two-layer aggregation tree automatically in exchanging process,which is used to realize basic information communication services.It provides AS administrative isolation for security and availability by guaranteeing path convergence for the same information in AS,and improves efficiency of communication.Meanwhile,it guarantees load balance between control nodes.Experiments verify that IEM has good performance.…”
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Resource Efficient Federated LoRaWAN Architecture for Far-Edge IoT Applications by Anna Triantafyllou, Ilias Siniosoglou, Vasileios Argyriou, Sotirios K. Goudos, Georgios Th. Papadopoulos, Konstantinos Panitsidis, Panagiotis Sarigiannidis

“…This study offers a comprehensive, implementable approach that tackles model scalability, and network-layer issues within a cohesive architecture, enhancing the practical implementation of AI-driven IoT deployments over LoRaWAN.…”
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A Refined Dual‐Fiber Network Morphology as Printable Hole Transport Layers for High‐Performance Perovskite Solar Mini‐Modules by Zhihui Yao, Qiyuan Xia, Jin Li, Xiangchuan Meng, Zengqi Huang, Muhammad Bilal Khan Niazi, Shaohua Zhang, Xiaotian Hu, Yiwang Chen

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DKA-YOLO: Enhanced Small Object Detection via Dilation Kernel Aggregation Convolution Modules by Yicheng Qiu, Feng Sha, Li Niu

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CAGNet: A Network Combining Multiscale Feature Aggregation and Attention Mechanisms for Intelligent Facial Expression Recognition in Human-Robot Interaction by Dengpan Zhang, Wenwen Ma, Zhihao Shen, Qingping Ma

“…To address these challenges, we propose CAGNet, a novel network that combines multiscale feature aggregation and attention mechanisms. …”
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A skin disease classification model based on multi scale combined efficient channel attention module by Hui Liu, Yibo Dou, Kai Wang, Yunmin Zou, Gan Sen, Xiangtao Liu, Huling Li

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LGM-Net: Wheat Pest and Disease Detection Network Based on Local Global Information Interaction and Multi-Level Feature Fusion by Yimin Qu, Shaobo Yu, Jing Yang

“…Secondly, this paper proposes a Multi-level Path Aggregation Network (MPA-Net), which uses the features output from all levels of the backbone network to construct a four-level node network that reduces layer by layer to improve the identification of multi-scale features in wheat pest and disease targets. …”
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OptWake-YOLO: a lightweight and efficient ship wake detection model based on optical remote sensing images by Runxi Qiu, Nan Bi, Chaoyue Yin

“…However, challenges persist due to sea surface interference, meteorological conditions, and coastal structures, while practical applications demand lightweight models with fast detection speeds.MethodsWe propose OptWake-YOLO, a lightweight ship wake detection model with three key innovations: A RepConv-based RCEA module in the Backbone combining efficient layer aggregation with reparameterization to enhance feature extraction. …”
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Location-Based Data Aggregation in 6LoWPAN by Jinyu Hu, Juan Luo, Yuxi Zhang, Panwu Wang, Yu Liu

“…To overcome these shortages, in this paper, we propose LDAA, a location-based novel data aggregation model that aggregates data from the network layer according to the MAC layer queuing delay. …”
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Enhancing Hierarchical Sales Forecasting with Promotional Data: A Comparative Study Using ARIMA and Deep Neural Networks by Mariana Teixeira, José Manuel Oliveira, Patrícia Ramos

“…Using a sales dataset from a major Portuguese retailer, base forecasts are generated for different hierarchical levels using ARIMA models and Multi-Layer Perceptron (MLP) neural networks. Reconciliation methods including bottom-up, top-down, and optimal reconciliation with OLS and WLS (struct) estimators are employed. …”
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Utilizing an Enhanced YOLOv8 Model for Fishery Detection by Hanyu Jiang, Jiacheng Zhong, Fuyu Ma, Cheng Wang, Ruiwen Yi

“…Additionally, we introduced the Channel Aggregation Efficient Downsampling Block (CAEDB) for more efficient upsampling and to improve the network’s expressive power and information flow through channel aggregation functionality. …”
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LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks by Bing Zhang, Haoyu Wang, Chao Ma, Hai Huang, Zhou Fang, Jiaxing Qu

“…To enhance the performance and stability of the Multilayer Perceptron model, we introduce a hidden layer called the aggregation layer in the Multilayer Perceptron model. …”
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