An Empirical Analysis of Transformer-Based and Convolutional Neural Network Approaches for Early Detection and Diagnosis of Cancer Using Multimodal Imaging and Genomic Data by S. K. B. Sangeetha, Sandeep Kumar Mathivanan, V. Muthukumaran, Jaehyuk Cho, and Sathishkumar Veerappampalayam Easwaramoorthy

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Retinopathy Disease Detection and Classification Using a Coordinate Attention Module-Based Convolutional Neural Network with Leaky Rectified Linear Unit by Pravin Balaso Chopade, Prabhakar N. Kota, Bhagvat D. Jadhav, Pravin Marotrao Ghate, Shriram Sadashiv Kulkarni

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Arouse-Net: Enhancing Glioblastoma Segmentation in Multi-Parametric MRI with a Custom 3D Convolutional Neural Network and Attention Mechanism by Haiyang Li, Xiaozhi Qi, Ying Hu, Jianwei Zhang

“…Addressing these challenges, this study introduces Arouse-Net, a 3D convolutional neural network that enhances feature extraction through dilated convolutions, improving tumor margin delineation. …”
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Deep learning-based malaria parasite detection: convolutional neural networks model for accurate species identification of Plasmodium falciparum and Plasmodium vivax by Diego A. Ramos-Briceño, Alessandro Flammia-D’Aleo, Gerardo Fernández-López, Fhabián S. Carrión-Nessi, David A. Forero-Peña

“…Artificial intelligence (AI) advances, particularly convolutional neural networks (CNNs), have significantly improved diagnostic capabilities and accuracy by enabling the automated analysis of medical images. …”
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Fake News Detection and Classification: A Comparative Study of Convolutional Neural Networks, Large Language Models, and Natural Language Processing Models by Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos

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Enhancing deep convolutional neural network models for orange quality classification using MobileNetV2 and data augmentation techniques by Phan Thi Huong, Lam Thanh Hien, Nguyen Minh Son, Huynh Cao Tuan, Thanh Q. Nguyen

“…This study introduces significant improvements in the construction of deep convolutional neural network models for classifying agricultural products, specifically oranges, based on their shape, size, and color. …”
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Papillary Thyroid Carcinoma Semantic Segmentation Using Multi-Scale Adaptive Convolutional Network With Dual Decoders by Thanat Payatsuporn, Pittipol Kantavat, Nichthida Tangnuntachai, Nopporn Tipparawong, Waratchanok Techapapa, Boonserm Kijsirikul, Somboon Keelawat

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Diagnosis of COVID-19 from Chest X-Ray Images Using Wavelets-Based Depthwise Convolution Network by Krishna Kant Singh, Akansha Singh

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Improved Convolutional Neural Image Recognition Algorithm based on LeNet-5 by Lijie Zhou, Weihai Yu

“…Convolutional neural network (CNN) is a very important method in deep learning, which solves many complex pattern recognition problems. …”
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Table Extraction with Table Data Using VGG-19 Deep Learning Model by Muhammad Zahid Iqbal, Nitish Garg, Saad Bin Ahmed

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FAULT DIAGNOSIS OF ROLLING BEARINGS BASED ON CHANNEL AND SPATIAL RECONSTRUCTION NETWORKS by ZHOU Tao, YAO DeChen, YANG JianWei

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Refined feature enhancement network for object detection by Zonghui Li, Yongsheng Dong

Subjects: “…Convolutional neural networks…”
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Predicting drug combination side effects based on a metapath-based heterogeneous graph neural network by Leixia Tian, Qi Wang, Zhiheng Zhou, Xiya Liu, Ming Zhang, Guiying Yan

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Eliminating Network Depth: Genetic Algorithm for Parameter Optimization in CNNs by M. Askari, S. Soleimani, M. H. Shakoor, M. Momeni

Subjects: “…Convolutional neural network…”
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Predicting correlation relationships of entities between attack patterns and techniques based on word embedding and graph convolutional network by Weicheng QIU, Xiuzhen CHEN, Yinghua MA, Jin MA, Zhihong ZHOU

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Improving source code suggestion with code embedding and enhanced convolutional long short‐term memory by Yasir Hussain, Zhiqiu Huang, Yu Zhou

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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

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Graph Convolution for Large-Scale Graph Node Classification Task Based on Spatial and Frequency Domain Fusion by Junwen Lu, Lingrui Zheng, Xianmei Hua, Yankun Wang

“…To address these issues, we propose a new GNN algorithm, LEGNN (Local and Global Enhanced Graph Neural Network), which introduces several key improvements over traditional GNN models such as GraphSAGE and GCN:Firstly, LEGNN combines a hybrid convolution method of spatial and spectral convolutions, enabling it to simultaneously capture local neighborhood relationships and global topological structures. …”
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Towards combining self-organizing maps (SOM) and convolutional neural network (CNN) for improving model accuracy: Application to malaria vectors phenotypic resistance by Komi Mensah Agboka, Elfatih M. Abdel-Rahman, Daisy Salifu, Brian Kanji, Frank T. Ndjomatchoua, Ritter A.Y. Guimapi, Sunday Ekesi, Landmann Tobias

Subjects: “…Combining Self-Organizing Maps (SOM) and Convolutional Neural Network (CNN) for improving model accuracy…”
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Pre-trained convolutional neural network with transfer learning by artificial illustrated images classify power Doppler ultrasound images of rheumatoid arthritis joints by Jun Fukae, Yoshiharu Amasaki, Yuichiro Fujieda, Yuki Sone, Ken Katagishi, Tatsunori Horie, Tamotsu Kamishima, Tatsuya Atsumi

“…Objective To study the classification performance of a pre-trained convolutional neural network (CNN) with transfer learning by artificial joint ultrasonography images in rheumatoid arthritis (RA). …”
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