Risk Prediction Algorithm of Social Security Fund Operation Based on RBF Neural Network by Linxuan Yang

“…This paper uses an improved ant colony algorithm to optimize the parameters of the RBF neural network, which overcomes the shortcomings of the traditional RBF neural network such as slow convergence, ease of falling into local extremes, and low accuracy, and improves the generalization ability of the RBF neural network. …”
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Verification of a static (off-line) signature using a convolutional neural network by U. Yu. Akhundjanov, V. V. Starovoitov

“…These images served as the source data for the convolutional neural network.As a result of testing the proposed approach, the average accuracy of the correct classification was achieved on medium-sized images and is equal to 93.33%.…”
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Energy-efficient analog-domain aggregator circuit for RRAM-based neural network accelerators by Khaled Humood, Yihan Pan, Shiwei Wang, Alexander Serb, Themis Prodromakis

“…Recently, there has been notable progress in the advancement of RRAM-based Compute-In-Memory (CIM) architectures, showing promise in accelerating neural networks with remarkable energy efficiency and parallelism. …”
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MSSA: multi-stage semantic-aware neural network for binary code similarity detection by Bangrui Wan, Jianjun Zhou, Ying Wang, Feng Chen, Ying Qian

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Retinal Thickness Asymmetry in Highly Myopic Eyes with Early Stage of Normal-Tension Glaucoma by Pei-Wen Lin, Hsueh-Wen Chang, Yi-Chieh Poon

“…To investigate the retinal thickness asymmetry parameters of circumpapillary retinal nerve fiber layer (cpRNFL) and macular layers measured by spectral-domain optical coherence tomography in highly myopic (HM) patients with an early stage of normal-tension glaucoma (NTG). Methods. This cross-sectional study included 55 eyes of HM patients with early NTG and 37 eyes of HM normal participants. …”
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Quadcopter Trajectory Tracking Based on Model Predictive Path Integral Control and Neural Network by Yong Li, Qidan Zhu, Ahsan Elahi

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Deep empirical neural network for optical phase retrieval over a scattering medium by Huaisheng Tu, Haotian Liu, Tuqiang Pan, Wuping Xie, Zihao Ma, Fan Zhang, Pengbai Xu, Leiming Wu, Ou Xu, Yi Xu, Yuwen Qin

“…Herein, we propose a concept of deep empirical neural network (DENN) that is a hybridization of a deep neural network and an empirical model, which enables seeing through an opaque scattering medium in an untrained manner. …”
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Automatic Detection of Cracks in Cracked Tooth Based on Binary Classification Convolutional Neural Networks by Juncheng Guo, Yuyan Wu, Lizhi Chen, Guanghua Ge, Yadong Tang, Wenlong Wang

“…Inspired by the achievements of applying deep convolutional neural networks (CNNs) in crack detection in engineering, this article proposes an image-based crack detection method using a deep CNN classifier in combination with a sliding window algorithm. …”
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Common and distinct neural underpinnings of the association between childhood maltreatment and depression and aggressive behavior by Yuan Li, Ting Zhang, Xin Hou, Xiaoyi Chen, Yu Mao

“…Abstract Background Although childhood maltreatment (CM) is widely recognized as a transdiagnostic risk factor for various internalizing and externalizing psychological disorders, the neural basis underlying this association remain unclear. …”
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A Novel Convolutional Neural Network-Based Approach for Fault Classification in Photovoltaic Arrays by Farkhanda Aziz, Azhar Ul Haq, Shahzor Ahmad, Yousef Mahmoud, Marium Jalal, Usman Ali

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Using Commercial Bio-Functional Fungal Polysaccharides to Construct Emulsion Systems by Associating with SPI by Laixin Dai, Qingfu Wang, Lining Wang, Qinghua Huang, Biao Hu

“…The association of either AAPs or GLPs with SPI enhanced the emulsion stability against coalescence and Ostwald ripening. Commercial fungal polysaccharides demonstrate substantial potential for incorporation into manufactured food products, particularly in colloidal formulations.…”
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Physics Informed Neural Networks for Modeling Large-Scale Wind Driven Ocean Circulation by Boohyun An, Mohammad Z. Shanti, Chan Yeob Yeun, Ernesto Damiani, Sungmun Lee, Tae-Yeon Kim

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Artificial neural networks and remote sensing in the analysis of the highly variable Pampean shallow lakes by Graciela Canziani, Rosana Ferrati, Claudia Marinelli, Federico Dukatz

Subjects: “…artificial neural network…”
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Fish oocyte morphology detection using neural networks: a comparison of YOLO architectures by Yanna Leidy Ketley Fernandes Cruz, Ewaldo Eder Carvalho Santana, Isa Rosete Araujo Nascimento, Antonio Fhillipi Maciel Silva, Raimunda Nonata Fortes Carvalho Neta, José Ribamar de Souza Torres-Junior

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Integral Transforms on a Function Space with Change of Scales Using Multivariate Normal Distributions by Dong Hyun Cho

“…In these evaluation formulas and integral transforms we use multivariate normal distributions so that the orthonormalization process of projection vectors which are needed to establish the conditional Wiener integrals can be removed in the existing change of scale transforms. …”
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Vehicle Attribute Recognition for Normal Targets and Small Targets Based on Multitask Cascaded Network by Fang Liu, Yong Zhang, Hua Gong, Ke Xu, Ligang Cai

“…For vehicle targets with normal size, the multitask cascaded convolution neural network MC-CNN-NT uses the improved Faster R-CNN as the location subnetwork. …”
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Prediction and Evaluation of Coal Mine Coal Bump Based on Improved Deep Neural Network by Shuang Gong, Yi Tan, Wen Wang

“…To predict coal bump disaster accurately and reliably, we propose a depth neural network (DNN) prediction model based on the dropout method and improved Adam algorithm. …”
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THE IMPACT OF NORMALIZATION PROCEDURES ON THE CLASSIFICATION OF BUILDING MATERIALS COMPANIES LISTED ON THE WARSAW STOCK EXCHANGE by Monika Zielińska-Sitkiewicz

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ECG Prediction Based on Classification via Neural Networks and Linguistic Fuzzy Logic Forecaster by Eva Volna, Martin Kotyrba, Hashim Habiballa

“…The paper deals with ECG prediction based on neural networks classification of different types of time courses of ECG signals. …”
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Multi-functional broadband diffractive neural network with a single spatial light modulator by Bolin Li, Yinfei Zhu, Jinlei Fei, Runshi Zheng, Min Gu, Jian Lin

“…Diffractive neural networks (DNNs) are emerging as a novel optical computing architecture that combines wave optics with deep-learning methods for high-speed parallel information processing. …”
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