MRM-BERT: a novel deep neural network predictor of multiple RNA modifications by fusing BERT representation and sequence features by Linshu Wang, Yuan Zhou

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Spectroscopic Method for Detection of Soluble Solid Content in Cherry Tomato Using Deep Convolutional Generative Adversarial Network-Based Data Augmentation by WU Zhijing, LIU Fuqiang, LI Zhigang, CHEN Hui

Subjects: “…cherry tomatoes; soluble solids content; visible-near-infrared spectroscopy; deep convolutional generative adversarial networks; one-dimensional convolutional neural networks…”
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SLG-Net: Small-Large-Global Feature-Based Multilevel Feature Extraction Network for Ultrasound Image Segmentation by Xinya Fan, Jianwen Hu, Kai Hu

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A multi-stage deep learning network toward multi-classification of polyps in colorectal images by Shilong Chang, Kun Yang, Yucheng Wang, Yufeng Sun, Chaoyi Qi, Wenlong Fan, Ying Zhang, Shuang Liu, Wenshan Gao, Jie Meng, Linyan Xue

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Deep Learning-Based Damage Assessment in Cherry Leaves by Burakhan Cubukcu, Hazel BOZCU

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Research on Recommendation Algorithm of Joint Light Graph Convolution Network and DropEdge by Haicheng Qu, Jiangtao Guo, Yanji Jiang

“…To mitigate these issues in a deep neural network-based recommendation algorithm, we propose a recommendation algorithm, LG-DropEdge, joint light graph convolutional network, and the DropEdge. …”
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AAT model based channel estimation for mmWave massive MIMO systems by Shujuan YU, Rong LIU, Yun ZHANG, Na XIE, Liya HUANG

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Comparative Analysis of Federated and Centralized Learning Systems in Predicting Cellular Downlink Throughput Using CNN by Kukuh Nugroho, Hendrawan, Iskandar

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Learning Spatial-Temporal Features of Ride-Hailing Services with Fusion Convolutional Networks by Dapeng Zhang, Feng Xiao, Gang Kou, Jian Luo, Fan Yang

“…In this paper, we propose a new deep learning framework, called the locally connected spatial-temporal fully convolutional neural network ( LC-ST-FCN), to learn the spatial-temporal correlations and local statistical differences among regions simultaneously. …”
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Secure Image Reconstruction using Deep Learning-based Autoencoder with Integrated Encryption Layers by Wurood Abd Ali

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NeuroSight: A Deep‐Learning Integrated Efficient Approach to Brain Tumor Detection by Shafayat Bin Shabbir Mugdha, Mahtab Uddin

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Correction: Pan et al. Identification of Buffalo Breeds Using Self-Activated-Based Improved Convolutional Neural Networks. <i>Agriculture</i> 2022, <i>12</i>, 1386 by Yuanzhi Pan, Hua Jin, Jiechao Gao, Hafiz Tayyab Rauf

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Reservoir Stochastic Simulation Based on Octave Convolution and Multistage Generative Adversarial Network by Xuechao Wu, Wenyao Fan, Shijie Peng, Bing Qin, Qing Wang, Mingjie Li, Yang Li

“…Also, a higher computing consumption and overfitting issue easily occurred by stacking Convolutional Neural Networks (CNNs). Therefore, a hybrid framework combined with octave convolution and multi-stage GAN (OctSinGAN) is proposed to perform reservoir simulation. …”
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Stock price prediction with attentive temporal convolution-based generative adversarial network by Ying Liu, Xiaohua Huang, Liwei Xiong, Ruyu Chang, Wenjing Wang, Long Chen

“…To address this issue, we propose a novel stock price prediction method based on the Generative Adversarial Networks (GANs) framework, utilizing an Attentive Temporal Convolutional Network (ATCN) as the generator, termed Attentive Temporal Convolution-based Generative Adversarial Network (ATCGAN). …”
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Klasifikasi Ekspresi Wajah Menggunakan Covolutional Neural Network by Ahmad Taufiq Akbar, Shoffan Saifullah, Hari Prapcoyo

“…Penelitian ini mengusulkan arsitektur sederhana Convolutional Neural Network (CNN) untuk meningkatkan efisiensi klasifikasi emosi pada dataset kecil. …”
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Solar Flare Forecasting Using Hybrid Neural Networks by Dan Xu, Pengchao Sun, Song Feng, Bo Liang, Wei Dai

“…We built two solar flare prediction models based on a combination of convolutional neural networks (CNN) and a temporal convolutional network (TCN), called CNN-TCN, and predicted whether a ≥C- or ≥M-class flare event would erupt in ARs in the next 24 hr, respectively. …”
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Neural network based image and video coding technologies by Chuanmin JIA, Zhenghui ZHAO, Shanshe WANG, Siwei MA

“…Deep neural networks have achieved tremendous success in artificial intelligence,which makes the broad and in-depth research of neural network resurge in recent years.Recently,the neural network based image and video coding has become one of the front-edge topics.A systematic and comprehensive review of neural network based image and video coding approaches based on network structure and coding modules were provided.The development of neural network based image compression,e.g.multi-layer perceptron,random neural network,convolutional neural network,recurrent neural network and generative adversarial network based image compression methods and neural network based video compression tools were introduced respectively.Moreover,the future trends in neural network based compression were also envisioned and discussed.…”
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Comparison of neural networks for suppression of multiplicative noise in images by V.A. Pavlov, A.A. Belov, V.T. Nguen, N. Jovanovski, A.S. Ovsyannikova

“…The paper compares several neural network (NN) architectures for suppression of multiplicative noise. …”
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Retracted: Image Recognition Technology Based on Neural Network by Jianqiu Chen

“…In this paper, the traditional classification algorithm based on convolutional neural network is improved, and the feature information of the key parts of the face is used to integrate the key part features with the global features of the face image to better distinguish similar categories. …”
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Application of adaptive ensemble neural network method for short-term load forecasting electrical engineering complex of regional electric grid by N. A. Serebryakov

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