An Extensive Study of Convolutional Neural Networks: Applications in Computer Vision for Improved Robotics Perceptions by Ravi Raj, Andrzej Kos

“…CNNs are developed to autonomously and effectively acquire spatial patterns of characteristics using backpropagation, leveraging an array of elements, including convolutional layers, pooling layers, and fully connected layers. …”
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Improving unsupervised pedestrian re‐identification with enhanced feature representation and robust clustering by Jiang Luo, Lingjun Liu

“…A global contrastive pooling (GCP) module is introduced to obtain the global features of the image. …”
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Climate Warming in the Eastern Mediterranean: A Comparative Analysis of Beirut and Zahlé (Lebanon, 1992–2024) by Rabih Zeinaldine, Salem Dahech

“…The Eastern Mediterranean region is experiencing accelerated climate warming, yet localized patterns remain poorly understood, particularly in areas with complex topography. …”
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Fault Diagnosis of Wind Turbine Blades Based on One-Dimensional Convolutional Neural Network-Bidirectional Long Short-Term Memory-Adaptive Boosting and Multi-Source Data Fusion by Kangqiao Ma, Yongqian Wang, Yu Yang

“…Fault data are first preprocessed by segmenting and labeling the fault patterns. Features are extracted through the convolutional layers, followed by dimensionality reduction and denoising using the pooling layers, and feature fusion. …”
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Image-Based Malware Detection Using Deep CNN Models by hawraa omran musa, Muhanad Tahrir Younis

“…The architecture of the proposed CNN primarily consists of more than one convolutional layer, max-pooling, dropout to mitigate overfitting problem, fully connected layers for achieving better classification results. …”
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META-GSA: Combining Findings from Gene-Set Analyses across Several Genome-Wide Association Studies. by Albert Rosenberger, Stefanie Friedrichs, Christopher I Amos, Paul Brennan, Gordon Fehringer, Joachim Heinrich, Rayjean J Hung, Thomas Muley, Martina Müller-Nurasyid, Angela Risch, Heike Bickeböller

“…The single marker association estimates of a predefined set of genes are either contrasted with those of all remaining genes or with a null non-associated background. To pool the p-values from several GSAs, it is important to take into account the concordance of the observed patterns resulting from single marker association point estimates across any given gene set. …”
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Leveraging U-Net and ASPP for effective fault detection in photovoltaic modules by Khalfalla Awedat, Masoud Alajmi, Mustafa Elfituri

“…This study presents a novel deep-learning-based approach to enhance fault detection in PV systems by customizing the Atrous Spatial Pyramid Pooling (ASPP) module within a U-Net architecture. …”
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Enhancement of Chest X-Ray Images to Improve Screening Accuracy Rate Using Iterated Function System and Multilayer Fractional-Order Machine Learning Classifier by Chia-Hung Lin, Jian-Xing Wu, Chien-Ming Li, Pi-Yun Chen, Neng-Sheng Pai, Ying-Che Kuo

“…The accuracy rate is thus improved. Pooling is performed to reduce the dimensions of the feature patterns and speed up complex computations. …”
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Navigating Nepal's health financing system: A road to universal health coverage amid epidemiological and demographic transitions. by Resham B Khatri, Pratik Khanal, Dipendra Singh Thakuri, Prabesh Ghimire, Mihajlo Jakovljevic

“…Key reforms  include: (1) merging or harmonizing existing social health protection schemes for efficient pooling and purchasing; (2) enhancing domestic health financing through increased health funding (≥5% of GDP) via payroll contributions, progressive taxation, and earmarked sin taxes; (3) reforming NHIP to mandatory enrollment starting from formal sector, subsidizing premium for informal sector and free coverage for disadvantaged groups, alongside strengthening policy implementation including accrediting of health facilities, ensuring service quality, prioritising and expanding coverage packages with strategic purchasing from all public and private health facilities; and (4) equitable public financing to ensure needs-based allocation across government levels that respond to demographic and epidemiological patterns. …”
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A multi-dilated convolution network for speech emotion recognition by Samaneh Madanian, Olayinka Adeleye, John Michael Templeton, Talen Chen, Christian Poellabauer, Enshi Zhang, Sandra L. Schneider

“…First, we use the Spatial Pyramid Pooling (SPP) strategy to remove the size constraint associated with the CNN-based image recognition task. …”
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Public-Private Partnership as a Model of Public Infrastructure Development by A. S. Bednyakov

“…A public-private partnership (PPP), a long-term pooling of public and private partners’ resources, sharing risks, responsibilities, and results, is a successful tool employed in many countries to develop public infrastructure. …”
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Deep convolutional neural network architecture for facial emotion recognition by Dayananda Pruthviraja, Ujjwal Mohan Kumar, Sunil Parameswaran, Vemulapalli Guna Chowdary, Varun Bharadwaj

“…By combining convolutional and pooling layers, the model effectively captures both subtle facial details and higher-level emotional patterns. …”
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Combining acoustic survey and citizen science data yields enhanced species distribution models for tropical rainforest birds. by Reid Rumelt, Carla Mere Roncal, Arianna Basto, Zuzana Buřivalová, Christopher Searcy

“…Our approach combined automated acoustic monitoring detections and eBird citizen science data available for the region as well as a high resolution land cover dataset of the region's key ecological gradients. The pooled models outperformed models constructed solely with eBird data for predicting fine grain species responses to habitat gradients in intact forest, but also retained information from the citizen science dataset about species occurrence patterns in non-vegetated areas away from intact forest, including those subject to human disturbance. …”
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Geographic variation in the determinants of ectoparasite faunas’ species richness: fleas and gamasid mites parasitic on small mammals from 6 biogeographic realms by Boris R. Krasnov, Vasily I. Grabovsky, Natalia Korallo-Vinarskaya, Maxim V. Vinarski, Angel Luis Robles Fernandez, Irina Khokhlova

“…We conclude that caution is needed in making judgements about the generality of macroecological patterns related to parasites based on the investigations of these patterns in limited numbers of localities and when pooling data on various taxa.…”
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Cross-Modal Complementarity Learning for Fish Feeding Intensity Recognition via Audio–Visual Fusion by Jian Li, Yanan Wei, Wenkai Ma, Tan Wang

“…Our framework incorporates dimension alignment strategies and attention mechanisms to capture temporal–spatial complementarity between acoustic feeding signals and visual behavioral patterns. Extensive experiments demonstrate superior performance compared to single-modal and conventional fusion approaches, with 6.4% accuracy improvement. …”
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Predicting changes in agricultural yields under climate change scenarios and their implications for global food security by Christine Li, James Camac, Andrew Robinson, Tom Kompas

“…We present updates to published estimates of crop yield responses to projected temperature, precipitation, and CO2 patterns and show that mixed effects models perform better than pooled OLS models on root mean squared error (RMSE) and explained deviance, despite the common usage of pooled OLS in previous meta-analyses. …”
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Research on Electric Vehicle Charging Load Prediction Methods Combining Signal Noise Reduction and Time Series Modeling by Liyun Liu, Xiaomei Xu, Jinsong Zhang, Dong Li

“…Subsequently, it employs convolutional and pooling layers within the CNN to reduce the dimensionality of the data, thereby optimizing the input dimensions. …”
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Advanced fault detection in photovoltaic panels using enhanced U-Net architectures by Khalfalla Awedat, Gurcan Comert, Mustafa Ayad, Abdulmajid Mrebit

“…Fault detection in photovoltaic (PV) panels using thermal images remains a significant challenge due to the complexity of thermal patterns, environmental noise, and the subtle nature of anomalies. …”
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ECG-GraphNet: Advanced arrhythmia classification based on graph convolutional networks by Myeonghun Lee, BS, Jiwoo Lim, MS, JinKook Kim, MS

“…A unique QRS-centered weighted average pooling method is employed to enhance beat-specific feature extraction. …”
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SAGEFusionNet: An Auxiliary Supervised Graph Neural Network for Brain Age Prediction as a Neurodegenerative Biomarker by Suraj Kumar, Suman Hazarika, Cota Navin Gupta

“…<b>Methods:</b> In this study, we propose SAGEFusionNet, a GNN architecture specifically designed to enhance brain age prediction and assess PD-related brain ageing patterns using T1-weighted structural MRI (sMRI). SAGEFusionNet learns important ROIs for brain age prediction by incorporating ROI-aware pooling at every layer to overcome the above challenges. …”
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