Convolutional neural networks to predict dispersion surfaces-based properties of acoustic metamaterials with arbitrary-shaped unit cells by Amirhossein Farajollahi, Mir Masoud Seyyed Fakhrabadi

“…This study presents a deep-learning framework for predicting and optimizing the bandgap properties of 2D acoustic metamaterials with arbitrary-shaped unit cells. …”
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Gramian Angular Field and Convolutional Neural Networks for Real-Time Multiband Spectrum Sensing in Cognitive Radio Networks by Yanqueleth Molina-Tenorio, Alfonso Prieto-Guerrero, Enrique Rodriguez-Colina, Luis Alberto Vásquez-Toledo, Omar Alejandro Olvera-Guerrero

“…This paper presents a distinctive framework where a central entity collects power spectral density data from multiple geographically distributed secondary users and applies the Gramian angular field (GAF) summation method to transform the time-series data into image representations. …”
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Constrained Heat Kernel Graph Diffusion Convolution: A High-Dimensional Statistical Approximation via Information Theory by Zhuo-Chen He

“…Our method demonstrates consistent performance improvements in downstream graph-mining tasks across six public datasets, offering a principled framework and faster approximation method for the diffusion time. …”
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Research on Intelligent Vehicle Tracking Control and Energy Consumption Optimization Based on Dilated Convolutional Model Predictive Control by Lanxin Li, Wenhui Pei, Qi Zhang

“…This model was then integrated into a model predictive control (MPC) framework. By solving a nonlinear optimization problem, a dilated convolutional model predictive controller (DCMPC) was developed to enhance tracking accuracy and reduce energy consumption. …”
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Optimizing forest stand aggregation in fragmented stands using graph convolutional networks: A case study in Japan by YangYu You, Hyun Bae Kim, Takuyuki Yoshioka

“…Unlike traditional rule-based methods that rely on fixed thresholds and static adjacency rules, the GCN framework allows stand-level attributes—such as slope, road proximity, and spatial adjacency—to influence each other through a graph structure. …”
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Robust Low-Snapshot DOA Estimation for Sparse Arrays via a Hybrid Convolutional Graph Neural Network by Hongliang Zhu, Hongxi Zhao, Chunshan Bao, Yiran Shi, Wenchao He

“…The C-GNN architecture combines 1D convolutional layers for local spatial feature extraction with graph convolutional layers for global structural learning, effectively capturing both fine-grained and long-range array dependencies. …”
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Breast tumor segmentation in ultrasound using distance-adapted fuzzy connectedness, convolutional neural network, and active contour by Marta Biesok, Jan Juszczyk, Pawel Badura

“…Abstract This study addresses computer-aided breast cancer diagnosis through a hybrid framework for breast tumor segmentation in ultrasound images. …”
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A Deep Learning Model Based on Bidirectional Temporal Convolutional Network (Bi-TCN) for Predicting Employee Attrition by Farhad Mortezapour Shiri, Shingo Yamaguchi, Mohd Anuaruddin Bin Ahmadon

“…In this study, we introduce a deep learning framework based on a Bidirectional Temporal Convolutional Network (Bi-TCN) to predict employee attrition. …”
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Comparative Analysis of Recurrent vs. Temporal Convolutional Autoencoders for Detecting Container Impacts During Quay Crane Handling by Sergej Jakovlev, Tomas Eglynas, Edvinas Pocevicius, Miroslav Voznak, Gediminas Gricius, Valdas Jankunas, Mindaugas Jusis

“…We compare the performance of Recurrent Autoencoders (RAEs) and Temporal Convolutional Autoencoders (TCAEs) using acceleration data collected during quay crane handling. …”
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Optimizing Fire Scene Analysis: Hybrid Convolutional Neural Network Model Leveraging Multiscale Feature and Attention Mechanisms by Shakhnoza Muksimova, Sabina Umirzakova, Mirjamol Abdullaev, Young-Im Cho

“…Extensive experiments on a comprehensive dataset encompassing wildfires, building fires, vehicle fires, and non-fire scenes demonstrate that the proposed framework outperforms existing cutting-edge techniques. …”
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Multi-Domain Feature Incorporation of Lightweight Convolutional Neural Networks and Handcrafted Features for Lung and Colon Cancer Diagnosis by Omneya Attallah

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GAGAN: Enhancing Image Generation Through Hybrid Optimization of Genetic Algorithms and Deep Convolutional Generative Adversarial Networks by Despoina Konstantopoulou, Paraskevi Zacharia, Michail Papoutsidakis, Helen C. Leligou, Charalampos Patrikakis

“…The discriminator, which classifies images as real or fake, is optimized not only through standard backpropagation, but also through a GA framework that evolves its weights via crossover, mutation, and selection processes. …”
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Modeling Higher-Order Interactions in Graphs Through Combinatorial Arc-Transitive Structure Using Graph Convolutional Network by Qingwei Wen

“…This research addresses the fundamental challenge of learning robust representations in heterophilic graphs by introducing Higher-Order Graph Convolutional Network (HiGCN), a novel framework that effectively models both homophilic and heterophilic interactions through a structured Petal-Complex (PC) model. …”
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Single Fringe Phase Retrieval for Translucent Object Measurements Using a Deep Convolutional Generative Adversarial Network by Jiayan He, Yuanchang Huang, Juhao Wu, Yadong Tang, Wenlong Wang

“…The network primarily relies on a generative adversarial network framework, with significant enhancements implemented in the generator network, including integrating the U-net++ architecture, Resnet101 as the backbone network for feature extraction, and a multilevel attention module for fully utilizing the high-level features of the source image. …”
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Prediction of Residual Life of Rolling Bearings Based on Multi-Scale Improved Temporal Convolutional Network (MITCN) Model by Keru Xia, Qi Li, Luyuan Han, Zhaohui Ren, Hengfa Luo

“…The model adopts the framework of a time convolution network and has good ability to extract time series information. …”
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ADMM-TransNet: ADMM-Based Sparse-View CT Reconstruction Method Combining Convolution and Transformer Network by Sukai Wang, Xueqin Sun, Yu Li, Zhiqing Wei, Lina Guo, Yihong Li, Ping Chen, Xuan Li

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Enhancing Surveillance Video Abnormal Behavior Detection Using Deep Convolutional Generative Adversarial Network With GRU Model by Setegn Asnakew Kasegn, Ronald Waweru Mwangi, Michael Kimwele, Surafel Lemma Abebe

“…This includes recent generative methods that use deep convolutional generative adversarial networks (DCGAN). …”
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MVBNSleepNet: A Multi-View Brain Network-Based Convolutional Neural Network for Neonatal Sleep Staging by Ligang Zhou, Minghui Liu, Xia Hu, Laishuan Wang, Yan Xu, Chen Chen, Wei Chen

“…<italic>Methods:</italic> We propose MVBNSleepNet, a multi-view brain network-based convolutional neural network. The framework integrates a multi-view brain network (MVBN) to characterize brain functional connectivity from linear temporal correlation, information-theoretic, and phase-dynamics perspectives, providing comprehensive spatial topological information. …”
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Monte Carlo-Based Strategy for Assessing the Impact of EEG Data Uncertainty on Confidence in Convolutional Neural Network Classification by Pierre Sedi Nzakuna, Vincenzo Gallo, Vincenzo Paciello, Aime Lay-Ekuakille, Angelo Kuti Lusala

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Weakly Supervised Semantic Segmentation of Mangrove Ecosystem Using Sentinel-1 SAR and Deep Convolutional Neural Networks by Arsalan Ghorbanian, Ardalan Ghorbanian, Seyed Ali Ahmadi, Ali Mohammadzadeh, Amin Naboureh

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