RESEARCH ON DEEP NEURAL NETWORK LEARNING BASED ON IMPROVED BP ALGORITHM by HUANG Pei

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Hierarchical Classification of Variable Stars Using Deep Convolutional Neural Networks by Mahdi Abdollahi, Nooshin Torabi, Sadegh Raeisi, Sohrab Rahvar

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Streamflow prediction using artificial neural networks and soil moisture proxies by Robert Edwin Rouse, Doran Khamis, Scott Hosking, Allan McRobie, Emily Shuckburgh

Subjects: “…artificial neural networks…”
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Double array system identification research based on LSTM neural network by Chunhua Gao, Mingyang Wang, Yifei Sima, Zihan Yuan

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Innovation of Urban Circular Economy Growth Path Based on Neural Network by Weifeng Qiu, Yi Yang

Subjects: “…Artificial neural network…”
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Research and application of prediction model based on ensemble BP neural network by Huimin ZHAO, Jiangtao LUO, Junchao YANG, Zheng XU, Xiao LEI, Lin LUO

Subjects: “…BP neural network…”
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Research on floating object classification algorithm based on convolutional neural network by Jikai Yang, Zihan Li, Ziyan Gu, Wei Li

Subjects: “…Convolutional Neural Network…”
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LANGUAGE SPACE OF NEURAL NETWORKS: FEATURES AND DIFFERENCES FROM NATURAL LANGUAGE by Natalia B. Egorchenkova, Olga V. Korobova

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Insolvency in Brazilian Football Clubs: Proposition of Models Based on Neural Networks by Fábio Minatto, José Alonso Borba

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Yogasana classification using Deep Neural Network: A Unique Approach by Rishi Raj, Rajesh Mukherjee, Bidesh Chakraborty

“…In this research work, we have automatically identified different Yogasanas from images using a deep neural network. For our work we have considered 10 very popular categories of Yogasana and built a dataset of volume 800 images. …”
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Sensory Precipitation Forecast Using Artificial Neural Networks and Decision Trees by Ünal Kızıl, Hakkı Fırat Altınbilek, Sefa Aksu, Hakan Nar

“…In the Decision Tree (DT) a model score of 0.96 was obtained by choosing the maximum depth of 20. The artificial neural network (ANN) yielded a classification score of 0.92 using 4 hidden layers and 100 epochs in the artificial neural network model.…”
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Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…This research presents a novel HAR system combining graph structures with deep neural networks to capture both spatial and temporal patterns in activities. …”
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THE REVIEW OF MECHANICAL FAULT DIAGNOSIS METHODS BASED ON CONVOLUTIONAL NEURAL NETWORK by WU DingHai, REN GuoQuan, WANG HuaiGuang, ZHANG YunQiang

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Implementasi Algoritma Convolutional Neural Network untuk Klasifikasi Jenis Keris by Maria Mediatrix Sebatubun, Cosmas Haryawan

“…Penelitian ini akan mengimplementasikan metode deep learning dengan algoritma Convolutional Neural Network (CNN) yang dapat melakukan tugas klasifikasi secara langsung pada citra, untuk membangun sebuah model untuk klasifikasi jenis keris berdasarkan dhapur. …”
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Discrete-Time Zhang Neural Networks for Time-Varying Nonlinear Optimization by Min Sun, Maoying Tian, Yiju Wang

“…As a special kind of recurrent neural networks, Zhang neural network (ZNN) has been successfully applied to various time-variant problems solving. …”
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Retracted: Nonlinear Autoregressive Neural Network for Antimicrobial Waste Water Treatment by Adsorption Science and Technology

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Convolutional Neural Network for Seizure Detection of Nocturnal Frontal Lobe Epilepsy by Fabio Pisano, Giuliana Sias, Alessandra Fanni, Barbara Cannas, António Dourado, Barbara Pisano, Cesar A. Teixeira

“…In this paper, an original Convolutional Neural Network (CNN) architecture is proposed to develop patient-specific seizure detection models for three patients affected by NFLE. …”
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Multitask Convolutional Neural Network for Rolling Element Bearing Fault Identification by Mingxing Jia, Yuemei Xu, Maoyi Hong, Xiyu Hu

“…To solve the abovementioned two problems, this paper proposes a fault-diagnosis algorithm based on “end-to-end” one-dimensional convolutional neural network. The one-dimensional convolution kernel and the pooling layer are directly applied to the original time domain signal. …”
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NLP neural network copyright protection based on black box watermark by Long DAI, Jing ZHANG, Xuefeng FAN, Xiaoyi ZHOU

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Nonintrusive Method Based on Neural Networks for Video Quality of Experience Assessment by Diego José Luis Botia Valderrama, Natalia Gaviria Gómez

“…In this paper, a model based on artificial neural networks such as BPNNs (Backpropagation Neural Networks) and the RNNs (Random Neural Networks) is applied to evaluate the subjective quality metrics MOS (Mean Opinion Score) and the PSNR (Peak Signal Noise Ratio), SSIM (Structural Similarity Index Metric), VQM (Video Quality Metric), and QIBF (Quality Index Based Frame). …”
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