Edge Computing Based on Convolutional Neural Network for Passenger Counting: A Case Study in Guadalajara, Mexico by Roxana Sánchez Laguna, Ulises Davalos-Guzman, Lina M. Aguilar-Lobo

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EHC-GCN: Efficient Hierarchical Co-Occurrence Graph Convolution Network for Skeleton-Based Action Recognition by Ying Bai, Dongsheng Yang, Jing Xu, Lei Xu, Hongliang Wang

“…In tasks such as intelligent surveillance and human–computer interaction, developing rapid and effective models for human action recognition is crucial. Currently, Graph Convolution Networks (GCNs) are widely used for skeleton-based action recognition. …”
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Multi-Signal Induction Motor Broken Rotor Bar Detection Based on Merged Convolutional Neural Network by Tianyi Wang, Shiguang Wen, Shaotong Sheng, Huimin Ma

“…The method preprocesses motor currents by Hilbert-Huang Transform (HHT) and Park’s Vector Modulus (PVM) and then uses a merged convolutional neural network (CNN) for classification. …”
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Adaptive Disconnector States Diagnosis Method Based on Adjusted Relative Position Matrix and Convolutional Neural Networks by Peifeng Yan, Chenzhang Chang, Dong Hua, Haomin Huang, Suisheng Liu, Peiyi Cui

“…In this paper, we propose an HVD state diagnosis method featuring adaptive recognition capabilities based on Fault Difference Signals, Adjusted Relative Position Matrix and Convolutional Neural Networks (FDS-ARPM-CNN). First, we align the measured operational power signal of the HVD drive motor with the recorded normal operational power signal, deriving the FDS through subtraction. …”
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Multilevel Assessment of Exercise Fatigue Utilizing Multiple Attention and Convolution Network (MACNet) Based on Surface Electromyography by Guofu Zhang, Banghua Yang, Peng Zan, Dingguo Zhang

“…Methods: This study proposes a multiple attention and convolution network (MACNet) for a three-level assessment of muscle fatigue based on sEMG. …”
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CNN-Based Detection of Sheath Incorrect Connection in the Cross-Bonded HV Cable Systems Using the Sheath Current Phasor Difference by Jing Tu, Zhanran Xia, Yongheng Ai, Ruoxin Song, Bin Yang, Changqun Sun, Xiaoyue Chi, Hang Wang

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Detection of Rat Pain-Related Grooming Behaviors Using Multistream Recurrent Convolutional Networks on Day-Long Video Recordings by Chien-Cheng Lee, Ping-Wing Lui, Wei-Wei Gao, Zhongjian Gao

“…Our model, a multistream recurrent convolutional network, learned to differentiate grooming from non-grooming behaviors within these clips through deep learning. …”
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Heterogeneous integration of 2D memristor arrays and silicon selectors for compute-in-memory hardware in convolutional neural networks by Samarth Jain, Sifan Li, Haofei Zheng, Lingqi Li, Xuanyao Fong, Kah-Wee Ang

“…The implemented full-hardware binary convolutional neural network (CNN) achieves remarkable accuracy (97.5%) in a pattern recognition task. …”
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Wavelet kernel and convolution neural network based accurate detection of incipient stator and rotor faults of induction motor by Sudeep Samanta, Jitendra Nath Bera, Amitava Biswas

“…By employing 14 mother wavelets as convolution filters, the method effectively extracts critical features from stator current signatures, streamlining the fault detection and classification process. …”
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Convolutional neural network for oral cancer detection combined with improved tunicate swarm algorithm to detect oral cancer by Xiao Wei, Liu Chanjuan, Jiang Ke, Ye Linyun, Gao Jinxing, Wang Quanbing

“…The current study employs a recently integrated model of an improved tunicate swarm algorithm to produce an efficient tool for improving a convolutional neural network and delivering an accurate cancer diagnostic system. …”
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Open-Circuit Fault Analysis and Recognition in Three-Level Inverters Based on Recurrence Plot and Convolution Neural Network by Jianjun Yan, Yanxing Huang, Shuai Yuan, Yufan Lu, Zeyu Yu

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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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Real-Time Series Arc Fault Detection and Appliances Classification in AC Networks Based on Competing Convolutional Kernels by Francesco Ferracuti, Riccardo Felicetti, Luca Cavanini, Patrick Schweitzer, Andrea Monteriu

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A cooperative intrusion detection system for internet of things using fuzzy logic and ensemble of convolutional neural networks by Xiongwei Qiu, Lianzhi Shi, Pengtong Fan

“…In this regard, our research presents a collaborative solution for intrusion detection in the IoT that relies on a combination of fuzzy logic techniques and Convolutional Neural Network (CNN) ensemble. Our goal is to solve the challenges in intrusion detection by using this combination and provide better performance in threat detection. …”
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Herbify: an ensemble deep learning framework integrating convolutional neural networks and vision transformers for precise herb identification by Farhan Sheth, Ishika Chatter, Manvendra Jasra, Gireesh Kumar, Richa Sharma

“…Utilizing transfer learning, the research harnessed pre-trained Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs), then integrated these models into an ensemble framework that leverages the unique strengths of each architecture. …”
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HMCFormer (hierarchical multi-scale convolutional transformer): a hybrid CNN+Transformer network for intelligent VIA screening by Bo Feng, Chao Xu, Zhengping Li, Chuanyi Zhang

“…In this article, we propose the Hierarchical Multi-Scale Convolutional Transformer network, which combines the hierarchical feature extraction capability of Convolutional Neural Network (CNNs) and the global dependency modeling capability of Transformers to address the challenges of realizing intelligent VIA screening. …”
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A graph convolutional network approach for hyperspectral image analysis of blueberries physiological traits under drought stress by Md. Hasibur Rahman, Savannah Busby, Sajid Hanif, Md Mesbahul Maruf, Faraz Ahmad, Sushan Ru, Alvaro Sanz-Saez, Jingyi Zheng, Tanzeel U. Rehman

“…To address this, a high-throughput phenotyping (HTPP) platform integrated with hyperspectral camera and a novel graph convolutional network (GCN)-based model, Plant-GCN, was developed to predict physiological traits of blueberry plants under drought stress. …”
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Convolutional Neural Networks Trained on Internal Variability Predict Forced Response of TOA Radiation by Learning the Pattern Effect by Maria Rugenstein, Senne VanLoon, Elizabeth A. Barnes

“…Abstract Predicting forced, long‐term radiative feedbacks from internal climate variability has been a decades‐long quest in climate science. We train a convolutional neural network (CNN) to predict annual‐ and global‐mean top of the atmosphere radiation anomalies from time‐varying maps of near‐surface temperature in climate models. …”
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Efficient Fault Localization in Smart Grid Through Analysis of the Wave Matrix Image Using Convolutional Neural Networks by Jose Carlos Filho, Francisco C. M. Abreu, Mauricio Silva, Fabbio Borges, Ricardo A. L. Rabelo

“…This article presents a methodology for fault localization in electric power distribution systems through the analysis of wave matrix image using Convolutional Neural Networks (CNN). Ensuring a continuous and high-quality supply of electric power is crucial for the efficient operation of a Power System. …”
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Transfer Learning to Detect COVID-19 Automatically from X-Ray Images Using Convolutional Neural Networks by Mundher Mohammed Taresh, Ningbo Zhu, Talal Ahmed Ali Ali, Asaad Shakir Hameed, Modhi Lafta Mutar

“…This study is aimed at evaluating the effectiveness of the state-of-the-art pretrained Convolutional Neural Networks (CNNs) on the automatic diagnosis of COVID-19 from chest X-rays (CXRs). …”
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