Convolutional neural network (CNN) based month’s name recognition in Gurumukhi script for Punjab state of India by Tajinder Pal Singh, Sheifali Gupta, Jamil Hussain, Sapna Juneja, Meenu Garg, Deepali Gupta, Majed Alsafyani

“…For this work, a dataset of 24,000 word images of 24 different Gurumukhi months has also been prepared from 500 distinct writers. …”
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MCTGNet: A Multi-Scale Convolution and Hybrid Attention Network for Robust Motor Imagery EEG Decoding by Huangtao Zhan, Xinhui Li, Xun Song, Zhao Lv, Ping Li

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Enhancing Recognition and Categorization of Skin Lesions with Tailored Deep Convolutional Networks and Robust Data Augmentation Techniques by Syed Ibrar Hussain, Elena Toscano

“…This study introduces deep convolutional neural network-based methods for the detection and classification of skin lesions, enhancing system accuracy through a combination of architectures, pre-processing techniques and data augmentation. …”
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Sparse convolutional neural network acceleration with lossless input feature map compression for resource‐constrained systems by Jisu Kwon, Joonho Kong, Arslan Munir

“…With several design optimization techniques, the authors have implemented their technique in a field‐programmable gate array (FPGA) system‐on‐chip platform and evaluated their technique for six different convolutional layers in SqueezeNet. Results reveal that the authors' technique improves the performance by 1.1×–22.6× while reducing energy consumption by 47.7%–97.4% as compared to the CPU‐based execution. …”
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Data-Driven Prediction of Grape Leaf Chlorophyll Content Using Hyperspectral Imaging and Convolutional Neural Networks by Minglu Zeng, Xinghui Zhu, Ling Wan, Jian Xu, Luming Shen

“…Subsequently, the study discussed 15 different spectral preprocessing methods, selecting fast Fourier transform (FFT) as the optimal approach. …”
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A road generalization method using graph convolutional network based on mesh-line structure unit by Tianyuan Xiao, Tinghua Ai, Dirk Burghardt, Pengcheng Liu, Min Yang, Aji Gao, Bo Kong, Huafei Yu

“…On the other hand, existing methods tend to consider individual structures separately in different algorithms, such as strokes, meshes and graph networks, lacking a solution that brings the advantages of these methods together. …”
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Convolutional neural network for the early identification of weeds: A technological support to biodiversity and yield losses mitigation by Claudio Russo, Valerio Cirillo, Marco Esposito, Matteo Lentini, Nausicaa Pollaro, Albino Maggio

“…With this study, we assessed the possibility of applying two convolutional neural networks (CNN) for the recognition of different classes of weeds in a winter wheat (T. aestivum) cultivation based on RGB images. …”
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A Spatiotemporal Convolutional Neural Network Model Based on Dual Attention Mechanism for Passenger Flow Prediction by Jinlong Li, Haoran Chen, Qiuzi Lu, Xi Wang, Haifeng Song, Lunming Qin

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Spatio-temporal Graph Convolutional Neural Network for traffic signal prediction in large-scale urban networks by Shimon Komarovsky, Jack Haddad

“…Different dataset and features are considered. In the first model, prediction of speed data is examined, while in the second model green times and speed are predicted. …”
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Research on Urban Road Traffic Flow Prediction Based on Sa-Dynamic Graph Convolutional Neural Network by Song Hu, Jian Gu, Shun Li

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A Novel Dilated Convolution Light Weight Neural Network (DCLW-NN) for the Classification of Breast Thermograms by S. Malathi, A. Shenbagavalli, N. Sriraam

“…The proposed model is experimented with two different infrared thermography imaging datasets like DMR-IR and Proprietary Datasets. …”
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LS-MambaNet: Integrating Large Strip Convolution and Mamba Network for Remote Sensing Object Detection by Lingyu Yan, Zijian He, Zhiqi Zhang, Guangqi Xie

“…In addition, a Multi-Granularity Spatial Mamba Block is proposed, and this employs a multi-granularity scanning strategy to reduce the computational cost and feature redundancy on different scanning paths and is able to efficiently model the global contextual information of the target. …”
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Identification of Fake Comments in E-Commerce Based on Triplet Convolutional Twin Network and CatBoost Model by Juanjuan Peng

“…To promote the development of e-commerce, a false comment recognition model based on triplet convolutional twin network and CatBoost model is proposed. …”
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Macro and mesoscopic mechanical behavior of concrete with actual aggregate segmented by hybrid Transformers and convolutional neural networks by Dong Wang, Junxing Zheng, Jichen Zhong, Lin Gao, Shuling Huang, Jiajia Zheng

“…A multi-branch parallel dilated convolutional feature fusion module is designed to effectively integrate multi-scale features from the different encoders. …”
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A convolutional neural network driven suspension control strategy to enhance sustainability of high-speed trains by Duo Zhang, Hong-Wei Li, Fang-Ru Zhou, Yin-Ying Tang, Qi-Yuan Peng

“…For addressing this challenge, a convolutional neural network driven control strategy is proposed for the suspension system of high-speed vehicles to simultaneously reduce energy consumption and carbody vibration on curved tracks. …”
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Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge by Karrar A. Kadhim, Farhan Mohamed, Fallah H Najjar, Ghalib Ahmed Salman

“… Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. …”
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Advancements and outlooks in utilizing Convolutional Neural Networks for plant disease severity assessment: A comprehensive review by Douglas Leite, Alisson Brito, Gregorio Faccioli

“…Following searches in six different databases and prominent conferences and the subsequent application of inclusion and exclusion criteria, this work analyzed 64 articles, addressing five specific review questions. …”
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A novel intelligent fault diagnosis method for gearbox based on multi-dimensional attention denoising convolution by Wei Liu, Zeqiao Zhang, Zhiwei Ye, Qiyi He

“…These data are not only contaminated by various types of noise but also exhibit fault features that vary across different scales. Consequently, the effective suppression of extraneous noise and accurate extraction of multi-scale fault features are crucial issues. …”
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Improving multi-talker binaural DOA estimation by combining periodicity and spatial features in convolutional neural networks by Reza Varzandeh, Simon Doclo, Volker Hohmann

“…The two-stage CNN incorporates a PD feature reduction stage prior to the joint processing of PD and CPS phase features. We investigate different design choices for the CNN architecture, including varying temporal reduction strategies and spectro-temporal filtering approaches. …”
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An efficient surface electromyography-based gesture recognition algorithm based on multiscale fusion convolution and channel attention by Bin Jiang, Hao Wu, Qingling Xia, Hanguang Xiao, Bo Peng, Li Wang, Yun Zhao

“…It uses fast dimensionality reduction, asymmetric convolution decomposition, and pooling to suppress the accumulation of parameters, then reducing the algorithmic complexity; The ECA is adopted to reweight the output features of Inception in different channels, enabling the RIE model to focus on information that is more relevant to gestures. 52-, 49-, and 52-class gesture recognition experiments are conducted on NinaPro DB1, DB3, and DB4 datasets, which contain 14,040, 3234, and 3120 gesture samples, respectively. …”
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