Cornell Potential: A Neural Network Approach by Halil Mutuk

“…We solved Schrödinger equation with Cornell potential (Coulomb-plus-linear potential) by using neural network approach. Four different cases of Cornell potential for different potential parameters were used without a physical relevance. …”
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Isolated word recognition using neural networks by Mark Filipovič

“…The system is based on feedforward neural networks trained by error backpropagation algorithm. …”
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The Use of Graph Databases for Artificial Neural Networks by Ahmet Cumhur Kınacı, Doğa Barış Özdemir

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Multilayer neural network model for unbalanced data by Xue ZHANG, Zhiguo SHI, Xuan LIU

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Artificial Neural Network in the CATS Training System by Yu. V. Popova

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ℋ∞ Stability Conditions for Fuzzy Neural Networks by Choon Ki Ahn

“…This paper presents a novel approach to assess the stability of fuzzy neural networks. First, we propose a new condition for the ℋ∞ stability of fuzzy neural networks. …”
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Free-space optical spiking neural network by Reyhane Ahmadi, Amirreza Ahmadnejad, Somayyeh Koohi

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Free-space optical spiking neural network. by Reyhane Ahmadi, Amirreza Ahmadnejad, Somayyeh Koohi

“…Among the various Optical Neural Networks (ONNs) explored within the realm of optical neuromorphic engineering, Spiking Neural Networks (SNNs) have exhibited notable success in emulating the computational principles of the human brain. …”
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Academic progress monitoring through neural network by Ramri Shukla, Bardia Khalilian, Sara Partouvi

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Attention-Aware Heterogeneous Graph Neural Network by Jintao Zhang, Quan Xu

Subjects: “…graph neural network (gnn)…”
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Regressions on quantum neural networks at maximal expressivity by Iván Panadero, Yue Ban, Hilario Espinós, Ricardo Puebla, Jorge Casanova, Erik Torrontegui

Subjects: “…Quantum neural networks…”
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Cognition: Differential-geometrical view on neural networks by S. A. Buffalov

Subjects: “…Neural network…”
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Computing nasalance with MFCCs and Convolutional Neural Networks. by Andrés Lozano, Enrique Nava, María Dolores García Méndez, Ignacio Moreno-Torres

“…A new approach is proposed to compute nasalance using Convolutional Neural Networks (CNNs) trained with Mel-Frequency Cepstrum Coefficients (mfccNasalance). mfccNasalance is evaluated by examining its accuracy: 1) when the train and test data are from the same or from different dialects; 2) with test data that differs in dynamicity (e.g. rapidly produced diadochokinetic syllables versus short words); and 3) using multiple CNN configurations (i.e. kernel shape and use of 1 × 1 pointwise convolution). …”
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Bearing Defect Detection with Unsupervised Neural Networks by Jianqiao Xu, Zhaolu Zuo, Danchao Wu, Bing Li, Xiaoni Li, Deyi Kong

“…The experiment of the unsupervised neural networks shows that the AUC of the model is 0.9721. …”
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Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

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Survey on backdoor attacks targeted on neural network by Qingyin TAN, Yingming ZENG, Ye HAN, Yijing LIU, Zheli LIU

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Evolving　Fuzzy　Neural　Networks　for　Extracting　Rules by He Zhenya Yao Susu Wei Chengjian (Department of Radio Engineering, Southeast University, Nanjing 210096)

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MODELING OF SOLAR RADIATION WITH A NEURAL NETWORK by VALENTIN STOYANOV, IVAYLO STOYANOV, TEODOR ILIEV

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Recent Developments on Time-Delay Neural Networks by Zheng-Guang Wu, Yun Chen, Xusheng Lei, Kun Liu, Hui Zhang

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Convolutional neural networks for diabetic retinopathy detection by Darwin Patiño-Pérez, Luis Armijos-Valarezo, Luis Chóez-Acosta, Freddy Burgos-Robalino

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