sEMG-Based Gesture Recognition Using Sigimg-GADF-MTF and Multi-Stream Convolutional Neural Network by Ming Zhang, Leyi Qu, Weibiao Wu, Gujing Han, Wenqiang Zhu

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A Transformer-Based Multiscale Difference Enhancement Network for Change Detection by Mengyang Pan, Hang Yang, Chengkang Yu, Mingqing Li, Anping Deng

“…Change detection (CD) is an important research field in remote sensing, aimed at identifying differences in multitemporal images. Despite the progress made by convolutional neural networks and Transformer architectures in visual analysis, challenges remain in achieving robust feature representation and global contextual understanding. …”
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Monte-Carlo Modelling For Evaluation Of Two Different Calculation Algorithms by Baljeet Seniwal, Telma C. F. Fonseca, Ranjit Singh

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Research on Detection of Icing Cover Transmission Lines Under Different Weather Conditions Based on Wide-Field Dynamic Convolutional Network LDKA-NET by Xinsheng Dong, Yuanhao Wan, Yongcan Zhu, Chao Ji

“…Secondly, a full-dimensional dynamic convolutional feature fusion network is proposed, which strengthens the model’s feature extraction ability by learning linear combinations of multiple convolution kernels and their weighted input-related attention. …”
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Convolutional neural network for maxillary sinus segmentation based on the U-Net architecture at different planes in the Chinese population: a semantic segmentation study by Jiayi Chen

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Rolling Bearing Fault Diagnosis Model Based on Multi-Scale Depthwise Separable Convolutional Neural Network Integrated with Spatial Attention Mechanism by Zhixin Jin, Xudong Hu, Hongli Wang, Shengyu Guan, Kaiman Liu, Zhiwen Fang, Hongwei Wang, Xuesong Wang, Lijie Wang, Qun Zhang

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Multi-scale sparse convolution and point convolution adaptive fusion point cloud semantic segmentation method by Yuxuan Bi, Peng Liu, Tianyi Zhang, Jialin Shi, Caixia Wang

“…To address these issues, this paper proposes a novel approach based on adaptive fusion of multi-scale sparse convolution and point convolution. First, addressing the drawbacks of redundant feature extraction with existing sparse 3D convolutions, we introduce an asymmetric importance of space locations (IoSL) sparse 3D convolution module. …”
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A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection by Noppadol Maneerat, Athasart Narkthewan, Kazuhiko Hamamoto

“…Different combinations of trained DCNNs were compared, and the combination with the maximum accuracy was retained as the winning combination. …”
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Performance Comparison of Different Pre-Trained Deep Learning Models in Classifying Brain MRI Images by Onur Sevli

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Combining Long-Term Recurrent Convolutional and Graph Convolutional Networks to Detect Phishing Sites Using URL and HTML by Subhash Ariyadasa, Shantha Fernando, Subha Fernando

“…This paper proposes PhishDet, a new way of detecting phishing websites through Long-term Recurrent Convolutional Network and Graph Convolutional Network using URL and HTML features. …”
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Normalized Difference Vegetation Index Prediction for Blueberry Plant Health from RGB Images: A Clustering and Deep Learning Approach by A. G. M. Zaman, Kallol Roy, Jüri Olt

“…In precision agriculture (PA), monitoring individual plant health is crucial for optimizing yields and minimizing resources. The normalized difference vegetation index (NDVI), a widely used health indicator, typically relies on expensive multispectral cameras. …”
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Learning Frequency-Aware Spatial Attention by Reconstructing Images With Different Frequency Responses by Keisuke Sano, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi

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Remaining Useful Life Prediction of Rolling Bearings Based on Multiscale Convolutional Neural Network with Integrated Dilated Convolution Blocks by Ran Wang, Ruyu Shi, Xiong Hu, Changqing Shen

“…Features from different receptive fields extracted by different sizes of convolution kernels can provide complete information for prognosis. …”
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Computing nasalance with MFCCs and Convolutional Neural Networks. by Andrés Lozano, Enrique Nava, María Dolores García Méndez, Ignacio Moreno-Torres

“…A new approach is proposed to compute nasalance using Convolutional Neural Networks (CNNs) trained with Mel-Frequency Cepstrum Coefficients (mfccNasalance). mfccNasalance is evaluated by examining its accuracy: 1) when the train and test data are from the same or from different dialects; 2) with test data that differs in dynamicity (e.g. rapidly produced diadochokinetic syllables versus short words); and 3) using multiple CNN configurations (i.e. kernel shape and use of 1 × 1 pointwise convolution). …”
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Multi-Semantic Alignment Graph Convolutional Network by Jisheng Qin, Xiaoqin Zeng, Shengli Wu, Yang Zou

“…Graph Convolutional Network (GCN) is a powerful emerging deep learning technique for learning graph data. …”
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Multiscale Convolutional Neural Networks for Hand Detection by Shiyang Yan, Yizhang Xia, Jeremy S. Smith, Wenjin Lu, Bailing Zhang

“…Deep learning models, and deep convolutional neural networks (CNNs) in particular, have achieved state-of-the-art performances in many vision benchmarks. …”
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Water Classification Using Convolutional Neural Network by Saira Asghar, Ghulam Gilanie, Mubbashar Saddique, Hafeez Ullah, Heba G. Mohamed, Irshad Ahmed Abbasi, Mohamed Abbas

“…The enhanced image samples were then fed to the proposed Convolutional Neural Network (CNN)-based model named WaterNet (WNet) for classification. …”
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MDIGCNet: Multidirectional Information-Guided Contextual Network for Infrared Small Target Detection by Luping Zhang, Junhai Luo, Yian Huang, Fengyi Wu, Xingye Cui, Zhenming Peng

Subjects: “…Difference convolution…”
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Characterization of saffron from different origins by HS-GC-IMS and authenticity identification combined with deep learning by Yingjie Lu, Chi Zhang, Kunmiao Feng, Jie Luan, Yuqi Cao, Khalid Rahman, Jianbo Ba, Ting Han, Juan Su

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Comparison of Preprocessing Method Impact on the Detection of Soldering Splashes Using Different YOLOv8 Versions by Peter Klco, Dusan Koniar, Libor Hargas, Marek Paskala

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