Land-sea Clutter Classification Method Based on Multi-channel Graph Convolutional Networks by Can LI, Zengfu WANG, Xiaoxuan ZHANG, Quan PAN

“…We propose a Multi-Channel Graph Convolutional Networks (MC-GCN) for land-sea clutter classification. …”
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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 light of these, we put forward a new way of diagnosing AD using magnetic resonance imaging (MRI) scans and transfer learned convolutional neural networks (CNN). Transfer learning makes it easier to reduce the costs involved in training and improves performance because it allows the use of models which have been trained previously and which generalize very well even when there is very little training data available. …”
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Intelligent Defect Identification Based on PECT Signals and an Optimized Two-Dimensional Deep Convolutional Network by Baoling Liu, Jun He, Xiaocui Yuan, Huiling Hu, Xuan Zeng, Zhifang Zhu, Jie Peng

“…To avoid the difficulty of manual feature extraction and overcome the shortcomings of the classic deep convolutional network (DCNN), such as large memory and high computational cost, an intelligent defect recognition pipeline based on the general Warblet transform (GWT) method and optimized two-dimensional (2-D) DCNN is proposed. …”
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Using deep convolutional networks combined with signal processing techniques for accurate prediction of surface quality by Mohammad Zangane, Mohammad Shahbazi, Seyed Ali Niknam

“…Finally, ShuffleNet was identified as an optimal architecture for real-time monitoring due to its accuracy, noise resilience, and low computational cost. In summary, this study demonstrates the capability of deep convolutional networks combined with innovative signal encoding techniques to accurately predict surface roughness values and categories under various cutting conditions. …”
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Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network by Nandita Goyal, Munesh Chandra Trivedi

“…The major goals of cloud computing include maximization of computing resources with minimization of cost. But the truth is that everything has a price and cloud computing is no different. …”
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Optical detection of beetle-related indicators and stem quality in roundwood using convolutional neural networks by Julia Achatz, Mark Schubert

“…Sorting wood based on macroscopic images using convolutional neural networks (CNN) is a cost-effective and efficient approach. …”
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DMCCT: Dual-Branch Multi-Granularity Convolutional Cross-Substitution Transformer for Hyperspectral Image Classification by Laiying Fu, Xiaoyong Chen, Yanan Xu, Xiao Li

“…In the field of hyperspectral image classification, deep learning technology, especially convolutional neural networks, has achieved remarkable progress. …”
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Domain Adversarial Convolutional Neural Network Improves the Accuracy and Generalizability of Wearable Sleep Assessment Technology by Adonay S. Nunes, Matthew R. Patterson, Dawid Gerstel, Sheraz Khan, Christine C. Guo, Ali Neishabouri

“…In this study, we applied a deep learning domain adversarial convolutional neural network (DACNN) model to this task and demonstrated that this new model outperformed existing sleep algorithms in classifying sleep–wake and estimating sleep outcomes based on wrist-worn accelerometry. …”
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Numerical Recognition Algorithm for Power Equipment Monitoring Based on Light-Resnet Convolutional Neural Network by Zhiheng KONG, Chong TAN, Peiyao TANG, Chengbo HU, Min ZHENG

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Classifying early-stage soybean fungal diseases on hyperspectral images using convolutional neural networks by Chieh Fu Hsiao, Georg Feyrer, Anthony Stein

“…Using convolutional neural networks (CNNs) to detect plant diseases has proven to reach high accuracy in the classification of infected and non-infected plant images. …”
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An enhanced light weight face liveness detection method using deep convolutional neural network by Swapnil R. Shinde, Anupkumar M. Bongale, Deepak Dharrao, Sudeep D. Thepade

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Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…This study investigates the use of two human-inspired algorithms—teaching learning-based optimization (TLBO) and student psychology-based optimization (SPBO)—to optimize convolutional neural networks (CNNs) for EEG-based drowsiness detection. …”
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Image-based yield prediction for tall fescue using random forests and convolutional neural networks by Sarah Ghysels, Bernard De Baets, Dirk Reheul, Steven Maenhout

“…The convolutional neural network outperformed the random forest method and exceeded the predictive power of the breeder’s eye. …”
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Hybrid Transformer–Convolutional Neural Network Approach for Non-Intrusive Load Analysis in Industrial Processes by Gengsheng He, Yu Huang, Ying Zhang, Yuanzhe Zhu, Yuan Leng, Nan Shang, Jincan Zeng, Zengxin Pu

“…This paper proposes a novel sequence-to-sequence-based non-intrusive load disaggregation method that integrates Convolutional Neural Networks (CNN) and Transformer architectures, specifically addressing the challenges of multi-device load disaggregation in industrial settings. …”
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The GAN Spatiotemporal Fusion Model Based on Multiscale Convolution and Attention Mechanism for Remote Sensing Images by Youping Xie, Jun Hu, Kang He, Li Cao, Kaijun Yang, Luo Chen

“…This article introduces a new generative adversarial network (GAN) spatiotemporal fusion model based on multiscale convolution and attention mechanism for remote sensing images (MSCAM-GAN), to generate high-resolution fused images. …”
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Klasifikasi Kualitas Biji Kedelai Menggunakan Transfer Learning Convolutional Neural Network Dan SMOTE by Amanda Prawita Ningrum, Sri Winarno, Vincentius Praskatama

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A Novel ViT Model with Wavelet Convolution and SLAttention Modules for Underwater Acoustic Target Recognition by Haoran Guo, Biao Wang, Tao Fang, Biao Liu

“…By introducing the Wavelet Transform Convolution (WTConv) module and the Simplified Linear Attention (SLAttention) module, WS-ViT can effectively extract spatiotemporal complex features, enhance classification accuracy, and significantly reduce computational costs. …”
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Rolling Bearing Life Prediction Based on Improved Transformer Encoding Layer and Multi-Scale Convolution by Zhuopeng Luo, Zhihai Wang, Xiaoqin Liu, Yingming Yang

“…Next, to further extract local temporal features within the bearing’s life cycle, a multi-scale convolution module is proposed to reinforce the local information across the entire lifespan. …”
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Klasifikasi Penyakit pada Tanaman Berdasarkan Citra Daun Menggunakan Metode Convolutional Neural Network by Denis Aji Pangestu, Okta Qomaruddin Aziz, Cahyo Crysdian

“…Plant disease identification typically requires experienced experts, but this process is time-consuming and costly. This research aims to develop a plant disease classification model using Convolutional Neural Network (CNN) to assist farmers in identifying diseases in rice, corn, tomato, and potato plants based on leaf images. …”
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Diagnosis Anthracnose of Chili Pepper Using Convolutional Neural Networks Based Deep Learning Models by Hae-In Kim, Ju-Yeon Yoon, Ho-Jong Ju

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