Neural networks utilization in the video game industry by V. V. Godin, A. E. Terekhova, D. N. Bulatov, I. А. Zaremba

Subjects: “…neural network…”
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A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…Thus, the fusion of Convolutional Neural Networks with Recurrent Neural Networks and Graph Networks enhances the efficiency of the detection process.…”
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Daily Prediction Model of Photovoltaic Power Generation Using a Hybrid Architecture of Recurrent Neural Networks and Shallow Neural Networks by Wilson Castillo-Rojas, Juan Bekios-Calfa, César Hernández

“…For the implementation of these models, a hybrid architecture based on recurrent neural networks (RNN) with long short-term memory (LSTM) or gated recurrent units (GRU) structure, combined with shallow artificial neural networks (ANN) with multilayer perceptron (MLP) structure, is established. …”
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Classification of Invoice Images By Using Convolutional Neural Networks by Sait Ali Uymaz, Ömer Arslan

Subjects: “…convolutional neural networks…”
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Influence of the Neural Network Hyperparameters on its Numerical Conditioning by S. V. Sholtanyuk

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Privacy leakage risk assessment for reversible neural network by Yifan HE, Jie ZHANG, Weiming ZHANG, Nenghai YU

Subjects: “…reversible neural network…”
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Finite-Time Synchronizing Control for Chaotic Neural Networks by Chao Zhang, Qiang Guo, Jing Wang

“…This paper addresses the finite-time synchronizing problem for a class of chaotic neural networks. In a real communication network, parameters of the master system may be time-varying and the system may be perturbed by external disturbances. …”
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Classification of diabetic retinopathy stages based on neural networks by M. M. Lukashevich, Y. I. Golub

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Finite-Time Robust Stabilization for Stochastic Neural Networks by Weixiong Jin, Xiaoyang Liu, Xiangjun Zhao, Nan Jiang, Zhengxin Wang

“…This paper is concerned with the finite-time stabilization for a class of stochastic neural networks (SNNs) with noise perturbations. The purpose of the addressed problem is to design a nonlinear stabilizator which can stabilize the states of neural networks in finite time. …”
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A flexible pruning on deep convolutional neural networks by Liang CHEN, Yaguan QIAN, Zhiqiang HE, Xiaohui GUAN, Bin WANG, Xing WANG

Subjects: “…convolutional neural network…”
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Tailoring convolutional neural networks for custom botanical data by Jamie R. Sykes, Katherine J. Denby, Daniel W. Franks

“…Methods We address this gap with informed data collection and the development of a new convolutional neural network architecture, PhytNet. Utilising a novel dataset of infrared cocoa tree images, we demonstrate PhytNet's development and compare its performance with existing architectures. …”
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A spiking neural network for active efficient coding by Thomas Barbier, Céline Teulière, Jochen Triesch

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Accelerating Deep Neural Networks implementation: A survey by Meriam Dhouibi, Ahmed Karim Ben Salem, Afef Saidi, Slim Ben Saoud

“…Deploying such Deep Neural Networks (DNN) on embedded devices is still a challenging task considering the massive requirement of computation and storage. …”
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Neural network decoding of the block Markov superposition transmission by Qianfan WANG, Sheng BI, Zengzhe CHEN, Li CHEN, Xiao MA

“…A neural network (NN)-based decoding algorithm of block Markov superposition transmission (BMST) was researched.The decoders of the basic code with different network structures and representations of training data were implemented using NN.Integrating the NN-based decoder of the basic code in an iterative manner,a sliding window decoding algorithm was presented.To analyze the bit error rate (BER) performance,the genie-aided (GA) lower bounds were presented.The NN-based decoding algorithm of the BMST provides a possible way to apply NN to decode long codes.That means the part of the conventional decoder could be replaced by the NN.Numerical results show that the NN-based decoder of basic code can achieve the BER performance of the maximum likelihood (ML) decoder.For the BMST codes,BER performance of the NN-based decoding algorithm matches well with the GA lower bound and exhibits an extra coding gain.…”
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Arrhythmia Classification Techniques Using Deep Neural Network by Ali Haider Khan, Muzammil Hussain, Muhammad Kamran Malik

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Convolutional Neural Network-Based Fish Posture Classification by Xin Li, Anzi Ding, Shaojie Mei, Wenjin Wu, Wenguang Hou

“…As such, the convolutional neural network (CNN) is introduced here to do classification and then to detect the fish’s posture. …”
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Research onconvolutional neural network for reservoir parameter prediction by You-xiang DUAN, Gen-tian LI, Qi-feng SUN

Subjects: “…artificial neural network…”
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Automatic Image Colorization Based on Convolutional Neural Networks by L. V. Serebryanaya, V. V. Potaraev

Subjects: “…artificial neural network…”
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Recursive Neural Networks Based on PSO for Image Parsing by Guo-Rong Cai, Shui-Li Chen

“…This paper presents an image parsing algorithm which is based on Particle Swarm Optimization (PSO) and Recursive Neural Networks (RNNs). State-of-the-art method such as traditional RNN-based parsing strategy uses L-BFGS over the complete data for learning the parameters. …”
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Generalization of neural network models for complex network dynamics by Vaiva Vasiliauskaite, Nino Antulov-Fantulin

“…A recently employed machine learning tool for studying dynamics is neural networks, which can be used for solution finding or discovery of differential equations. …”
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