Establishment and Test Effect of Artificial Intelligence Optimization Model Based on Convolutional Neural Network by Chunrong Zhou, Zhenghong Jiang

“…In addition, the authors optimized the convolutional layer, pooling layer, and loss function of AL-CNN in different parameters, which improved the stability of noise processing, respectively. …”
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Analysis of MSTAR Object Classification Features Extracted by a Deep Convolutional Neural Network by I. F. Kupryashkin

“…Introduction. Deep convolutional neural networks are effective tools for classifying objects on radar images; however, their decision-making process is not transparent. …”
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Enhancing market trend prediction using convolutional neural networks on Japanese candlestick patterns by Edrees Ramadan Mersal, Kürşat Mustafa Karaoğlan, Hakan Kutucu

“…Subsequently, the model was trained and evaluated multiple times using different combinations of these subsets. This method allows for a more accurate assessment of the model’s predictive capabilities by examining its performance on unseen data.…”
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Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation by Quentin Malé, Corentin J. Lapeyre, Nicolas Noiray

“…Our data-driven approach leverages a Convolutional Neural Network (CNN), trained to approximate filtered burning rates from emulated LES data. …”
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Real-Time Transformer Detection of Underwater Objects Based on Lightweight Gated Convolutional Network by Yuhui LI, Huixia CUI, Yaomin LI, Senping JIA

“…To address the challenges in underwater object detection algorithms, including difficult image feature processing, redundant model architectures, and excessive parameter numbers, this paper proposed a real-time Transformer detection method for underwater objects based on a lightweight gated convolutional network. This method first constructed a convolutional gated linear unit based on the gating mechanism to dynamically modulate feature transmission. …”
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Convolutional Neural Networks for Real Time Classification of Beehive Acoustic Patterns on Constrained Devices by Antonio Robles-Guerrero, Salvador Gómez-Jiménez, Tonatiuh Saucedo-Anaya, Daniela López-Betancur, David Navarro-Solís, Carlos Guerrero-Méndez

“…Recent research has demonstrated the effectiveness of convolutional neural networks (CNN) in assessing the health status of bee colonies by classifying acoustic patterns. …”
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A Multi-Scale Feature Fusion Hybrid Convolution Attention Model for Birdsong Recognition by Lianglian Gu, Guangzhi Di, Danju Lv, Yan Zhang, Yueyun Yu, Wei Li, Ziqian Wang

“…The integration of multi-scale feature extraction and fusion enables the model to better handle scale variations, thereby enhancing its adaptability across different scales. To address this issue, we propose a multi-scale hybrid convolutional attention mechanism model (MUSCA). …”
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Soil moisture forecasting in wireless sensor networks via spatiotemporal graph convolutional networks by Weixuan Wang, Yating Wei, Longfei Hao, Zushuai Wei, Tianjie Zhao

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Preprocessing-Free Convolutional Neural Network Model for Arrhythmia Classification Using ECG Images by Chotirose Prathom, Ryuhi Fukuda, Yuto Yokoyanagi, Yoshifumi Okada

“…Machine learning models have been developed to classify arrhythmia using electrocardiogram (ECG) data, which effectively capture the patterns associated with different abnormalities and achieve high classification performance. …”
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Rotation-Invariant Convolution With Point Sort and Curvature Radius for Point Cloud Classification and Segmentation by Zhao Shen, Xin Jia, Jinglei Zhang

“…(i) Similar distances and angles among different points would lead to ambiguous descriptions of local regions. …”
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Efficient Recognition of the Propagated Orbital Angular Momentum Modes in Turbulences With the Convolutional Neural Network by Zikun Wang, Maxime Irene Dedo, Kai Guo, Keya Zhou, Fei Shen, Yongxuan Sun, Shutian Liu, Zhongyi Guo

“…Recently, convolutional neural network (CNN), as a model of deep learning, has been widely applied to machine vision. …”
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Advanced Temporal Convolutional Network Framework for Intrusion Detection in Electric Vehicle Charging Stations by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, It Ee Lee, Muhammad Sheraz, Eng Eng Ngu, Teong Chee Chuah

“…The proposed Temporal Convolutional Network (TCN)-based Intrusion Detection System (IDS) architecture integrates four key innovations: multi-receptive fields, a gating mechanism, iterative dilation, and a self-attention mechanism combined with a Squeeze-and-Excitation (SE) block to recalibrate feature responses by explicitly modeling interactions between different channels. …”
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Spatial Multifeature and Dual-Layer Multihop Graph Convolution Networks for Hyperspectral Image Classification by Xiangyue Yu, Ning Li, Di Wu, Zheng Li, Zhenyuan Wu, Ximing Ma

“…Specifically, a dual-layer multihop graph convolutional network is constructed within the GCN branch, which can take the features of superpixel at different segmentation scales as network nodes to effectively capture and fuse the superpixel features in HSI. …”
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A fine-tuned convolutional neural network model for accurate Alzheimer’s disease classification by Muhammad Zahid Hussain, Tariq Shahzad, Shahid Mehmood, Kainat Akram, Muhammad Adnan Khan, Muhammad Usman Tariq, Arfan Ahmed

“…In this research, we used three different pre-trained CNN based architectures (AlexNet, GoogleNet, and MobileNetV2) each implemented with several solvers (e.g. …”
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Classification of Toraja Wood Carving Motif Images Using Convolutional Neural Network (CNN) by Nurilmiyanti Wardhani, Billy Eden William Asrul, Antonius Riman Tampang, Sitti Zuhriyah, Abdul Latief Arda

“…Image processing approaches, particularly the development of Convolutional Neural Networks (CNN), offer a solution for extracting information from the diverse and intricate patterns of Toraja wood carvings. …”
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Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks by Ahmed Mateen Buttar, Zubair Shaheen, Abdu H. Gumaei, Mogeeb A. A. Mosleh, Mogeeb A. A. Mosleh, Indrajeet Gupta, Samah M. Alzanin, Muhammad Azeem Akbar

“…This study introduces a deep learning framework designed to automate neuro-diagnostics, addressing the limitations of current manual interpretation methods, which are often time-consuming and prone to variability.MethodsWe propose a specialized deep convolutional neural network (DCNN) framework aimed at detecting and classifying neurological anomalies in MRI data. …”
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Bangladeshi Vehicle Classification and Detection Using Deep Convolutional Neural Networks With Transfer Learning by Farid, Proshanta Kumer Das, Monirul Islam, Ebna Sina

“…Finally, we have tested the proposed Bangladeshi vehicle detection system with different timing, lighting, and weather conditions in several areas of Dhaka city. …”
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Automatic Potato Crop Beetle Recognition Method Based on Multiscale Asymmetric Convolution Blocks by Jingjun Cao, Xiaoqing Xian, Minghui Qiu, Xin Li, Yajie Wei, Wanxue Liu, Guifen Zhang, Lihua Jiang

“…Specifically, it comprises several multiscale asymmetric convolution blocks, which are designed to extract features at multiple scales, mainly by integrating different-sized asymmetric convolution kernels in parallel. …”
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Application of convolutional neural networks trained on optical images for object detection in radar images by V.A. Pavlov, A.A. Belov, S.V. Volvenko, A.V. Rashich

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System Development for Liquid Chemicals Point Injection Based on Convolutional Neural Network Models by V. S. Semenyuk, E. A. Nikitin

“…In practice, it could differ from the declared one by no more than 10-15 percent. …”
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