CGV-Net: Tunnel Lining Crack Segmentation Method Based on Graph Convolution Guided Transformer by Kai Liu, Tao Ren, Zhangli Lan, Yang Yang, Rong Liu, Yuantong Xu

“…Lining cracking is among the most prevalent forms of tunnel distress, posing significant threats to tunnel operations and vehicular safety. …”
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Severe-hail detection with C-band dual-polarisation radars using convolutional neural networks by V. Forcadell, V. Forcadell, C. Augros, O. Caumont, O. Caumont, K. Dedieu, M. Ouradou, C. David, J. Figueras i Ventura, O. Laurantin, H. Al-Sakka

“…<p>Radar has consistently been proven to be the most reliable source of information for the remote detection of hail within storms in real time. …”
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Enhancing Early Exit Performance With Uncertainty-Aware Training in Convolutional Neural Networks for Image Classification by Thanu Kurian, Somasundaram Thangam

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Exploring Applications of Convolutional Neural Networks in Analyzing Multispectral Satellite Imagery: A Systematic Review by Antonia Ivanda, Ljiljana Šerić, Maja Braović

“…Today is possible to extract features specific to various fields of application with the application of modern machine learning techniques, such as Convolutional Neural Networks (CNN) on MultiSpectral Images (MSI). …”
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SignFormer-GCN: Continuous sign language translation using spatio-temporal graph convolutional networks. by Safaeid Hossain Arib, Rabeya Akter, Sejuti Rahman, Shafin Rahman

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An Efficient Method for Diagnosing Brain Tumors Based on MRI Images Using Deep Convolutional Neural Networks by Thanh Han-Trong, Hinh Nguyen Van, Huong Nguyen Thi Thanh, Vu Tran Anh, Dung Nguyen Tuan, Luu Vu Dang

“…In the next step, Deep Convolutional Neural Networks are used and then we propose to apply ADAS optimization function to build predictive models based on that normalized dataset. …”
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A Spiking Neural Network With Adaptive Graph Convolution and LSTM for EEG-Based Brain-Computer Interfaces by Peiliang Gong, Pengpai Wang, Yueying Zhou, Daoqiang Zhang

“…Moreover, most are designed for specific BCI tasks and lack some generality. …”
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Advanced holographic convolutional dense networks and Tangent runner optimization for enhanced polycystic ovarian disease classification by Prathibanandhi Jeyashanker, Annie Grace Vimala Georgewilliam Sundaram, Padmakala Sadagopan, Abid Yahya, Ravi Samikannu, Irfan Anjum Badruddin, Sarfaraz Kamangar, Mohamed Ghouse Shukur

“…Abstract Polycystic Ovarian Disease (PCOD) is among the most prevalent endocrine disorders complicating the health of innumerable women worldwide due to lack of diagnosis and appropriate management. …”
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A Convolutional Neural Network Model for Classifying Resting Tremor Amplitude in Parkinson&#x2019;s Disease by Augusto Ielo, Serena Dattola, Lilla Bonanno, Paolo De Pasquale, Alberto Cacciola, Angelo Quartarone, Maria Cristina De Cola

“…Resting tremor (RT) is one of the most common and debilitating symptoms of Parkinson&#x2019;s Disease (PD), characterized by involuntary rhythmic muscle contractions. …”
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An Efficient 3D Convolutional Neural Network for Dose Prediction in Cancer Radiotherapy from CT Images by Lam Thanh Hien, Pham Trung Hieu, Do Nang Toan

“…<b>Introduction</b>: Cancer is a highly lethal disease with a significantly high mortality rate. One of the most commonly used methods for treatment is radiation therapy. …”
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Bayesian-Optimized Convolutional Neural Networks for Classifying Primary Tumor Origin of Brain Metastases from MRI by Jawed Nawabi, Semil Eminovic, Alexander Hartenstein, Georg Lukas Baumgaertner, Nils Schnurbusch, Madhuri Rudolph, David Wasilewski, Julia Onken, Eberhard Siebert, Edzard Wiener, Georg Bohner, Andrea Dell'Orco, Mike P. Wattjes, Bernd Hamm, Uli Fehrenbach, Tobias Penzkofer

“…<b>Background/Objectives</b>: This study evaluates whether convolutional neural networks (CNNs) can be trained to determine the primary tumor origin from MRI images alone in patients with metastatic brain lesions. …”
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Effects of scale on segmentation of Nissl–stained rat brain tissue images via convolutional neural networks by Alexandro Arnal, Olac Fuentes

“…Currently, it is not clear what scale of the input tissue images offers the most information for these models to exploit. In this work, we test a fully convolutional architecture, U–Net, with Nissl–stained rat brain tissue images of different scales. …”
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A Lightweight Convolutional Neural Network to Predict Steering Angle for Autonomous Driving Using CARLA Simulator by Imtiaz Ul Hassan, Huma Zia, H. Sundus Fatima, Syed Adnan Yusuf, Muhammad Khurram

“…End-to-end learning for autonomous driving uses a convolutional neural network (CNN) to predict the steering angle from a raw image input. …”
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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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FCN attention enhancing asphalt pavement crack detection through attention mechanisms and fully convolutional networks by Huiyuan Zhang, Jiawei Liu, Guoping Hu

“…Abstract This paper presents an innovative approach to detecting cracks in asphalt pavement using an FCN-attention model, which integrates attention mechanisms into a fully convolutional network (FCN) for enhanced pixel-level segmentation. …”
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Evenness and hairiness measurement of chenille yarn based on an improved pixel difference convolution for the pixel difference network by Chenghan Yang, Yun Xu, Jianpeng Zhang, Jianxin Zhang

“…To address the challenge of quality measurement in fancy yarns, an improved Pixel Difference Convolution (PDC) for the Pixel Difference Network (PiDiNet) is proposed for measuring the evenness and hairiness of chenille yarn. …”
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Extracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints by Fenghui Lian, Yingjie Sun, Meiyu Li

“…Specifically, for the auxiliary constraint, a set of convolutional structures are involved into a conventional network to act as a discriminator, then adversarial network is established. …”
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Robust Classification of Encrypted Network Services Using Convolutional Neural Networks Optimized by Information Bottleneck Method by Zhijiong Wang, Wei Lin, Yu Chen, Mang I. Vai

“…This paper proposes a novel approach to achieve robust classification of encrypted network services using Convolutional Neural Networks (CNNs) optimized by the Information Bottleneck (IB) method (IB-CNN). …”
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Enhanced Coronary Artery Disease Classification Through Feature Engineering and One-Dimensional Convolutional Neural Network by Atitaya Phoemsuk, Vahid Abolghasemi

“…The proposed method works based on a one-dimensional convolutional neural network (1D-CNN), offering a cost-effective alternative for sophisticated cardiac health monitoring. …”
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Identification and Classification of Atmospheric Particles Based on SEM Images Using Convolutional Neural Network with Attention Mechanism by Changchang Yin, Xuezhen Cheng, Xilu Liu, Meng Zhao

“…It is necessary to study the classification method of atmospheric particles with higher accuracy. In this paper, a convolutional neural network (CNN) model with attention mechanism is proposed to identify and classify the scanning electron microscopy (SEM) images of atmospheric particles. …”
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