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• Medical Image Segmentation using a Self-organizing Neural Network and Clifford Geometric Algebra
  In this paper we present a method based on self-organizing neural networks to extract the shape of an object which is useful for segmentation tasks. For that, the method uses a set of transformations expressed as versors in the conformal geometric algebra fram…
  crossref J. Rivera-Rovelo, E. Bayro-Corrochano 2008-07-18T15:34:22Z 置信度 0.70
• Designing a Muscle like System Based on PID Controller and Tuned by Neural Network
  This paper presents a study on a muscle like system based on a PID controller tuned by a neural network. The approach is based on a non linear muscle model using system identification based on a NNARX (neural network autoregressive exogenous) structure. This m…
  crossref H.J. Serhan, C.G. Nasr, P. Henaff 2006-10-30T12:35:23Z 置信度 0.70
• CM-Net: a point cloud upsampling network based on adversarial neural network
  In the real-life application scenarios, the collected point clouds are often sparse, noisy and non-uniform, especially if the application is unable to capture the local spatial layout due to the lack of points. Thus, point cloud upsampling aims to transform sp…
  crossref Xiaomeng Li, Chung-Ming Own, Kaizhen Wu, Qian Sun 2021-09-20T21:27:41Z 置信度 0.70
• Content-based Video Adaptation in Low/Variable Bandwidth Communication Networks Using Adaptable Neural Network Structures
  In this paper, an adaptable neural network model is used for real time video delivery over communication networks of low and variable bandwidth, such as the wireless ones. The scheme performs video delivery in content domain in contrast to the previous approac…
  crossref A. Doulamis, G. Tziritas 2008-07-18T11:34:22Z 置信度 0.70
• Artificial Neural Network (ANN) in Network Reconfiguration for Improvement of Voltage Stability
  Issues related to power system voltage levels have become increasingly important issue during last two and half decades. In power networks, low voltage situations may result in the loss of stability, voltage collapse and eventually to cascading power outages. …
  crossref Dipu Sarkar, Joyanta Kumar Roy 2019-09-18T13:52:17Z 置信度 0.70
• Detecting dynamical changes within a simulated neural ensemble using a measure of representational quality
  Technological advances allowing simultaneous recording of neuronal ensembles have led to many developments in our understanding of how the brain performs neural computations. One key technique for extracting information from neural populations has been populat…
  crossref Jadin C Jackson, A David Redish 2015-08-18T20:04:06Z 置信度 0.70
• Study of a learning algorithm for neural networks with discrete synaptic couplings
  The authors present a new learning algorithm for neural networks with discrete synaptic couplings. The main difference with respect to other previous algorithms is that it is defined in the continuous space. Its performance and features are analysed in detail.
  crossref C J Pérez Vicente, J Carrabina, E Valderrama 2015-08-18T16:04:12Z 置信度 0.70
• Neural Network Black Box Approach to the Modeling and Control of Dynamical Systems
  crossref Yury V. Tiumentsev, Mikhail V. Egorchev 2019-06-21T15:36:10Z 置信度 0.70
• A comparative analysis of Feed-forward neural network & Recurrent Neural network to detect intrusion
  As computer networks are grows exponentially security in computer system has become a foremost issue. Monitoring atypical activity can be one way to detect any violation that impedes computer systems security. Existing methods like statistical models [12] for …
  crossref Nipa Chowdhury, Mohammod Abul kashem 2009-01-29T16:44:06Z 置信度 0.70
• Efficient stereo coding in the multiscale representation*
  crossref Zhaoping Li, Joseph Atick 2002-08-25T02:35:54Z 置信度 0.70
• Network Architecture
  crossref Dean A. Pomerleau 2011-06-15T05:55:34Z 置信度 0.70
• NEURAL-NETWORK-BASED GENETIC ALGORITHM FOR OPTIMAL KITCHEN FAUCET STYLES
  Artificial neural networks (ANNs) are the models of choice in many data classification tasks.In this study, ANN classification models were used to explore user perceptions about kitchen faucet styles and investigate the relations between the overall preference…
  crossref Fehmi Burcin Ozsoydan, Celal Murat Kandemir, Ezgi Aktar Demirtas 2015-09-29T06:43:31Z 置信度 0.70
• Incremental Gain Analysis of Chaotic Recurrent Neural Network and Applications in Pattern Association
  Chaotic neural networks have been successfully applied in pattern association problems in many research. However there are few in-depth theoretical analysis for such networks, such as stability issues. In this paper, we propose a new type of chaotic recurrent …
  crossref Wu Yilei, Song Qing, Liu Sheng 2008-07-18T11:34:22Z 置信度 0.70
• Artificial Neural Network Model for Friction Stir Processing
  Abstract — Friction stir processing (FSP) is an effective means of refining grain size of aluminum alloys. An artificial neural network model (ANN) is made for predicting the grain size of alloys which are processed by FSP. The simulated results from the model…
  crossref Syed Muhammed Fahd 2015-12-24T10:45:10Z 置信度 0.70
• Gene Expression Dataset Classification Using Artificial Neural Network and Clustering-Based Feature Selection
  With the progression of bioinformatics, applications of GE profiles on cancer diagnosis along with classification have become an intriguing subject in the bioinformatics field. It holds numerous genes with few samples that make it arduous to examine and proces…
  crossref Audu Musa Mabu, Rajesh Prasad, Raghav Yadav 2021-09-17T11:47:50Z 置信度 0.70
• Neural Network Based Detection of Melanoma Skin Cancer
  The sensitivity and specificity for diagnosis of melanoma achieved by neural network analysis of Raman spectra were 85% and 99%, respectively. We propose that neural network analysis of near-infrared Fourier transform Raman spectra could provide a novel method…
  crossref 2016-06-15T18:01:00Z 置信度 0.70
• A Neural Network based Technique for Automatic Classification of Road Cracks
  This paper presents a neural network based technique for the classification of segments of road images into cracks and normal images. The density and histogram features are extracted. The features are passed to a neural network for the classification of images…
  crossref J. Bray, B. Verma, Xue Li, W. He 2008-07-18T11:34:22Z 置信度 0.70
• The Modified Differential Evolution and the RBF (MDE-RBF) Neural Network for Time Series Prediction
  We develop a modified differential evolution algorithm that produces radial basis function neural network controllers for chaotic systems. This method requires few controlling variables. We examine the result of applying the proposed algorithm to time series p…
  crossref H. Dhahri, Adel.M. Alimi 2008-07-18T15:34:22Z 置信度 0.70
• Comparison on Zhang neural network and gradient neural network for time-varying linear matrix equation AXB = C solving
  For solving online the linear matrix equation AXB = C with time-varying coefficients, this paper presents a special kind of recurrent neural networks by using a design method recently proposed by Zhang et al. Compared with gradient neural networks (abbreviated…
  crossref Yunong Zhang, Ke Chen 2008-08-28T05:34:49Z 置信度 0.70
• Predicting Missing Regions in Charged Particle Tracks Using a Sparse 3D Convolutional Neural Network
  The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light s…
  crossref Hilary Utaegbulam 2024-08-15T02:30:21Z 置信度 0.70
• Unsupervised learning for Boltzman Machines
  An unsupervised learning algorithm for a stochastic recurrent neural network based on the Boltzmann Machine architecture is formulated in this paper. The maximization of the mutual information between the stochastic output neurons and the clamped inputs is use…
  crossref Gustavo Deco, Lucas Parra 2015-08-18T16:04:47Z 置信度 0.70
• Regulating the nonlinear dynamics of olfactory cortex
  The dynamic behaviour of cortical structures can be changed significantly in character by different types of neuromodulators. We simulate such effects in a neural network model of the olfactory cortex and analyse the resulting nonlinear dynamics of this system…
  crossref Xiangbao Wu, Hans Liljenstrom 2002-08-25T02:35:54Z 置信度 0.70
• Evolving neurocontrollers for balancing an inverted pendulum
  This paper introduces an evolutionary algorithm that is tailored to generate recurrent neural networks functioning as nonlinear controllers. Network size and architecture, as well as network parameters like weights and bias terms, are developed simultaneously.…
  crossref F Pasemann 2015-08-18T16:04:53Z 置信度 0.70
• Controlling chaos with a neural network
  Chaotic situations may occur in complex systems as a normal operating mode or may accidentally be induced due to a change in some system parameter. The author reports one approach to the use of feedforward networks to dampen chaotic oscillations in Duffing's o…
  crossref T.W. Frison 2003-01-02T11:19:33Z 置信度 0.70
• Multilayer Performance Improvement of Feedforward Neural Networks
  crossref 2022-12-01T03:35:42Z 置信度 0.70
• An associative memory network for identifying mingling odors
  crossref 2003-04-25T01:05:53Z 置信度 0.70
• A Fully CMOS Low-Cost Chaotic Neural Network
  A chaotic IC is proposed and fabricated using a 0.35μm CMOS technology. The circuit iterates an N-shaped transfer function that can be modified using two external voltages, and is implemented using a three neurons network. The main advantages of the proposed c…
  crossref J.L. Rossello, S. Bota, V. Canals, I. de Paul 等 2008-07-18T11:27:21Z 置信度 0.70
• Neural Network Unit Density: A Critical Biological Parameter
  crossref N. Azmy, J.-F. Vibert 2013-12-09T03:06:39Z 置信度 0.70
• Figure 3: Anomaly detection method based on multimodal neural network.
  crossref 2025-06-30T04:37:54Z 置信度 0.70
• Botnet Detection Mechanism Using Graph Neural Network
  Botnet Detection Mechanism Based On Graph Neural Network Aleksander Maksimoski, 2023. Master of Applied Science Computer Networks Toronto Metropolitan University, Toronto, Ontario, Canada. A botnet is a group of computers that are infected by malware, which ca…
  crossref Aleksander Masimoski 2025-12-04T18:45:26Z 置信度 0.70
• Figure 9: Results of neural network training, iterations 2,001–4,000.
  crossref 2023-11-13T04:21:26Z 置信度 0.70
• Figure 7: Competitive neural network architecture used for data classification.
  crossref 2021-08-02T03:14:48Z 置信度 0.70
• Neural Network Analysis, Architectures and Applications
  From the Publisher: This book describes techniques for extracting what has been learnt by a trained neural network. The book also describes some novel neural network architectures, and some sample applications of neural computing systems.
  crossref A Browne 2024-12-10T09:11:09Z 置信度 0.70
• Convolution Neural Network Based Image Recognition
  The identification of an image is one thorny task in computer vision problems. Using the python programming language and a few other machine learning algorithms and python libraries, this image recognition and feature extraction can be achieved. In pattern- an…
  crossref Sofia Hamid, Mrigana Walia 2024-12-06T08:52:19Z 置信度 0.70
• An ETF Trading Decision Support System by Using Neural Network and Technical Indicators
  This paper proposed a neural network based decision support system (DSS) to provide investors with suggestions on transaction timing and transaction strategies of Taiwan 50 index exchange traded funds (ETF). Various indicators were employed with corresponding …
  crossref Chih-Lung Chen, Mu-Hsing Kuo 2008-07-18T15:34:22Z 置信度 0.70
• Feature Extraction Using an Unsupervised Neural Network
  crossref Nathan Intrator 2018-12-26T09:22:20Z 置信度 0.70
• Twofold type of backpropagation neural network
  Various types of neural networks have been introduced and those have been used in various areas. In some areas, those operate in a very good manner, but in another they don't. For example, Boltzmann machine and Hopfield network have better estimation and analo…
  crossref S. Sugiyama 2002-11-19T13:30:57Z 置信度 0.70
• Systolic Simulation of Hamming Neural Network
  The paper describes the systolic simulation of Hamming net algorithm. Systolic arrays creation methodology is based on Data Dependence Graphs analysis. The proposed implementation is focused on completely digital circuits. Input data is passed through the neur…
  crossref Jacek Mazurkiewicz 2013-03-11T00:11:40Z 置信度 0.70
• Multiplicative neural noise can favor an independent components representation of sensory input
  Arguments have been advanced to support the role of principal components (e.g., Karhunen-Loéve, eigenvector) and independent components transformations in early sensory processing, particularly for color and spatial vision. Although the concept of redundancy r…
  crossref Allan Gottschalk, Matthew G Sexton, Guilherme Roschke 2015-08-18T20:04:00Z 置信度 0.70
• Neural Network Based Constitutive Modelling of Inelastic Materials
  New materials that are associated with novel micro-structures are becoming available at a rapid speed. The mechanical characteristics of solid materials are studied using constitutive models. The formulation of constitutive relations is challenging and may be …
  crossref Reem Alhayki 2024-05-24T14:19:06Z 置信度 0.70
• Video for HBUCNNA: Hybrid Binary-Unary Convolutional Neural Network Accelerator
  crossref 2020-09-29T09:22:27Z 置信度 0.70
• Deep Neural Network Modeling of Electric Motors
  Modélisation, contrôle et supervision de moteurs électriques par réseaux de neurones profonds Cette thèse traite de l’application des réseaux de neurones dans la résolution de problèmes liés aux moteurs électriques. Le chapitre 2 contribue à identifier une stru…
  crossref Sagar Verma 2026-04-07T17:11:55Z 置信度 0.70
• Fig. 7. Cluster N 4 of the sensorimotor neural network
  crossref 2024-11-08T05:20:05Z 置信度 0.70
• Bitcoin candlestick price prediction with recurrent neural network
  Bitcoin is a high-risk asset with a potentially high return. Predicting Bitcoin candlestick, i.e., open, high, low, and close (OHLC) prices, can help investors make trading decisions. The objective of this study is to develop a neural network model to predict …
  crossref Sutiwat Simtharakao 2023-09-15T06:04:40Z 置信度 0.70
• All-optical neural network with nonlinear activation functions
  991012994404403412 HKUST Electronic Theses All-optical neural network with nonlinear activation functions by Zuo Ying thesis 2021 1 online resource (xxiii, 130 pages) : illustrations (some color) Artificial neural networks (ANNs) have now been widely used for …
  crossref Ying Zuo 2022-02-16T21:38:45Z 置信度 0.70
• Neural Network Models
  crossref Philippe De Wilde 2013-06-11T00:02:07Z 置信度 0.70
• BP Neural Network
  crossref 2011-01-10T09:40:51Z 置信度 0.70
• Session 3: Neural networks in biomedical applications
  crossref 2010-12-09T15:34:50Z 置信度 0.70
• Enhanced Malaria Detection Using Convolutional Neural Networks with SHAP and LIME for Model Interpretability
  Malaria is a major global health concern in low-resource countries. Artificial intelligence (AI), particularly convolutional neural networks (CNNs), has become an effective approach for the automatic identification of malaria in blood smear images. However, th…
  crossref Souaad Hamza Cherif, Zineb Aziza Elaouaber, Lamia Fatiha Kazi Tani, Adil Gaouar 等 2025-08-25T20:15:01Z 置信度 0.70
• Neural Network Modeling of the Weather Prediction Task
  crossref Minjeong Kim 2022-09-07T22:15:25Z 置信度 0.70
• Botnet Detection Mechanism Using Graph Neural Network
  Botnet Detection Mechanism Based On Graph Neural Network Aleksander Maksimoski, 2023. Master of Applied Science Computer Networks Toronto Metropolitan University, Toronto, Ontario, Canada. A botnet is a group of computers that are infected by malware, which ca…
  crossref Aleksander Masimoski 2025-12-04T18:45:25Z 置信度 0.70
• Table 4: Comparison of human and neural network annotation performance.
  crossref 2024-10-22T05:11:48Z 置信度 0.70
• Text Recognition using Multilayer Perceptron Neural Network
  This work focuses on development of an Offline Hand Written English Character Recognition algorithm based on Artificial Neural Network (ANN). The ANN implemented in this work has single output neuron which shows whether the tested character belongs to a partic…
  crossref Khushal Gupta 2024-12-07T08:13:46Z 置信度 0.70
• A Neural Network Approach to Dependent *Reliability Estimation.
  This research presents the creation of a new model for automating the generation of component and system reliability estimates from simulated field data for tightly coupled systems. The model utilizes the CMAC neural network architecture, which resembles the h…
  crossref Roya Javadpour 2022-06-13T21:35:52Z 置信度 0.70
• Figure 1: Artificial neural network architectures used for cancer classification.
  crossref 2020-04-13T06:23:21Z 置信度 0.70
• Neural Network
  crossref 2006-07-10T11:34:18Z 置信度 0.70
• DYAN-bicycleGAN
  With the rapid development of neural networks and computer vision, video prediction has become a topic of interest. Inspired by the GAN related image-to-image translation network, this work addresses the challenge by modeling the dynamic information in a video…
  crossref Huaiyu Zheng 2021-05-10T17:10:59Z 置信度 0.70
• Supervised classification on deep neural network attack toolchains
  Deep learning, while an important machine learning technique, is susceptible to adversarial example attacks. Adversarial examples generated by adding perturbations on clean images/video frames can lead to mis-predictions of deep neural networks. Moreover, deep…
  crossref Yize Li 2022-08-24T14:53:21Z 置信度 0.70
• Figure 4. Architecture of the developed artificial neural network models.
  crossref 2024-05-11T04:27:42Z 置信度 0.70
• Fig. 6. Cluster N 3 of the sensorimotor neural network
  crossref 2024-11-08T05:20:05Z 置信度 0.70
• Algorithm 1: Ant colony optimization with graph neural network embeddings.
  crossref 2026-01-09T08:00:28Z 置信度 0.70
• Artificial Neural Network and Fuzzy Neural Network Algorithm for Financial Health Analysis of Indonesian SOEs
  The determining of financial soundness of SOEs company is regulated by the government through Decree of the Minister of SOEs KEP: 100 / BUMN / 2002. There are 8 parameters to be calculated for determining financial soundness such as ROE, ROI, cash ratio, curre…
  crossref 2021-04-22T05:46:03Z 置信度 0.70
• Change-based inference for invariant discrimination
  Under a conventional view of information processing in recurrently connected populations of neurons, computations consist in mapping inputs onto terminal attractor states of the dynamical interactions. However, there is evidence that substantial information re…
  crossref Reza Moazzezi, Peter Dayan 2008-10-22T21:05:27Z 置信度 0.70
• Artificial neural network (ANN) - oscillatory neural network (ONN) hybrid system using domain-wall synapse devices and nano-constriction spin hall nano oscillators
  crossref Anonymous 2026-08-19T17:56:37Z 置信度 0.70
• Local Interpretability Methods for Time Series Modeling
  <p>Interpretability aims to improve our understanding of the model behavior. Local interpretability methods can explain the specific predictions of a model and create trust between the model and its users, empowering the practitioners with powerful new i…
  crossref Ozan Ozyegen 2024-06-19T00:51:44Z 置信度 0.70
• Software Reliability Analysis by Using the Bidirectional Attention Based Zeiler-Fergus Convolutional Neural Network
  Software quality assurance relies heavily on software reliability as one of its primary metrics. Numerous studies have been conducted to identify the software reliability. Improved software dependability may be studied using a triangular approach that includes…
  crossref Dorai Samy Sudharson, Ramalingam Gomathi, Lakshmanan Selvam 2024-04-23T07:17:03Z 置信度 0.70
• PATIENT-ADAPTED AND INTER-PATIENT ECG CLASSIFICATION USING NEURAL NETWORK AND GRADIENT BOOSTING
  Heart disease diagnosis is an important non-invasive technique. Therefore, there exists an effort to increase the accuracy of arrhythmia classification based on ECG signals. In this work, we present a novel approach of heart arrhythmia detection. The model con…
  crossref Lukáš Zaorálek, Jan Platoš, Václav Snášel 2018-07-16T04:09:03Z 置信度 0.70
• Associative memory for patterns with different bias
  A neural network model for the storage of patterns with different biases is considered analytically. When introducing an optimized external field the model reaches the theoretically maximal storage capacity in the limit of strong bias. The information processi…
  crossref H Englisch, M Herrmann 2002-08-24T22:35:54Z 置信度 0.70
• Optimal Rule Induction in Neural Networks
  crossref G. D. Tattersall 2013-12-09T03:06:39Z 置信度 0.70
• A neural network for image understanding
  crossref Heggere S Ranganath, Govindaraj Kuntimad, John L Johnson 2004-11-26T05:22:16Z 置信度 0.70
• Feedback-Error-Learning Neural Network for Supervised Motor Learning
  crossref Mitsuo Kawato 2014-07-01T06:36:05Z 置信度 0.70
• Enhancing the Understandability and Interpretability of Type-II Diabetes Diagnosis Using a Deep Fuzzy Neural and XAI Approach
  Deep fuzzy neural applications have been shown to be effective in improving the accuracy of type-II diabetes diagnosis. However, due to their inherent complexity, deep fuzzy neural applications are often not easy to explain and communicate between doctors and …
  crossref Min-Chi Chiu, Tin-Chih Toly Chen, Hsin-Chieh Wu 2025-07-22T18:00:51Z 置信度 0.70
• Graph Neural Network for Multi-Physics Geothermal Simulation with Discrete Fracture Network
  crossref Manojkumar Gudala, Bicheng Yan 2025-01-11T15:39:59Z 置信度 0.70
• The neural network algorithm-based quality assessment method for university English translation
  These results highlight the transformative potential of neural network algorithms in providing consistency and transparency while reducing the inherent subjectivity in human evaluations, revolutionizing translation quality assessment in academia. The findings …
  crossref Min Gong 2024-04-24T05:04:56Z 置信度 0.70
• Genetic Algorithm (GA) and Internal Energy Transfer Calculations Using Neural Network (NN) Methods
  Genetic algorithms (GA), like NNs, can be used to fit highly nonlinear functional forms, such as empirical interatomic potentials from a large ensemble of data. Briefly, a genetic algorithm uses a stochastic global search method that mimics the process of natu…
  crossref Lionel Raff, Ranga Komanduri, Martin Hagan, Satish Bukkapatnam 2020-11-11T01:32:27Z 置信度 0.70
• Traffic signal control - a neural network approach
  Artificial Neural Networks (ANNs) have been proven to be an important development in a variety of problem solving areas. Increasing research activity in ANN applications has been accompanied by equally rapid growth in the commercial mainstream use of ANNs. How…
  crossref Gerard Nivard Cadet 2017-11-13T23:45:51Z 置信度 0.70
• An Artificial Neural Network for Bankruptcy Prediction
  Assessing the financial health of organizations remains a topic of great interest to economists, financial institutions, and invested stakeholders. For more than a century, research into financial distress has focused primarily on traditional applications of s…
  crossref Walter D Magdefrau 2024-01-09T21:23:24Z 置信度 0.70
• Ionospheric single-station TEC short-term forecast using RBF neural network
  In this article a radial basis function (RBF) neural network improved by Gaussian mixture model is developed to be used for forecasting ionospheric 30 min total electron content (TEC) data given the merits of its nonlinear modeling capacity. In order to unders…
  crossref Z. Huang, H. Yuan 2014-03-21T22:24:52Z 置信度 0.70
• RBF Neural Network Control Based on Gradient Descent Algorithm
  crossref Jinkun Liu 2013-01-24T23:15:56Z 置信度 0.70
• Learning temporal sequences by local synaptic changes
  The authors consider fully connected neural networks in which synaptic weights are continuously slightly updated according to the activity of their pre- and post-synaptic neurons. The synaptic weights change slowly and therefore, at any time, the network behav…
  crossref Y Metzger, D Lehmann 2002-07-26T19:51:19Z 置信度 0.70
• Learning with two sites of synaptic integration
  Since the classical work of D O Hebb 1949 The Organization of Behaviour (New York: Wiley) it is assumed that synaptic plasticity solely depends on the activity of the pre- and the post-synaptic cells. Synapses influence the plasticity of other synapses exclusi…
  crossref Konrad Körding, Peter König 2002-08-25T02:35:54Z 置信度 0.70
• PERBANDINGAN PERFORMA PREDIKSI TINGKAT KEMISKINAN ANTARA BACKPROPAGATION NEURAL NETWORK DAN GENERALIZED REGRESSION NEURAL NETWORK
  Menurunkan tingkat kemiskinan penduduk merupakan suatu program kerja Pemerintah Indonesia yang hingga saat ini masih berlangsung. Pemberian bantuan secara merata, tepat dan cepat merupakan salah satu upaya pemerintah dalam menangani masalah kemiskinan. Upaya t…
  crossref Rina Mamase, Ruli S. Sinukun 2018-11-29T00:34:26Z 置信度 0.70
• Backpropagation Neural Network as Earthquake Early Warning Tool using a new Elementary Modified Levenberg–Marquardt Algorithm to minimise Backpropagation Errors
  Abstract. A new Elementary Modified Levenberg–Marquardt Algorithm (M-LMA) was used to minimise backpropagation errors in training a backpropagation neural network (BPNN) to predict the records related to the Chi-Chi earthquake from four seismic stations, Stati…
  crossref Jyh-Woei Lin, Chun-Tang Chao, Juing-Shian Chiou 2018-05-09T08:12:41Z 置信度 0.70
• ASSESSMENT OF PARKINSON'S DISEASE PROGRESSION USING NEURAL NETWORK AND ANFIS MODELS
  Patients suffering from Parkinson's disease must periodically undergo a series of tests, usually performed at medical facilities, to diagnose the current state of the disease.Parkinson's disease progression assessment is an important set of procedures that sup…
  crossref Jakub Hlavica, Michal Prauzek, Tomáš Peterek, Petr Musílek 2016-05-13T04:17:30Z 置信度 0.70
• Artifical neural network model for rainfall-runoff relationship
  Artificial neural networks (ANNs) have emerged as an alternative approach in modeling the runoff process in which the explicit form of the relationship between the variables involved is unknown. This thesis focuses on the implementation of artificial neural ne…
  crossref Prem Junsawang 2025-03-19T01:41:55Z 置信度 0.70
• Incorporating physical knowledge into deep neural network
  Incorporation de connaissance physique dans des réseaux de neurones profonds Un processus physique est un phénomène marqué par des changements graduels à travers une série d'états successifs se produisant dans le monde physique. Les physiciens et les climatolo…
  crossref Arthur Pajot 2026-04-04T02:52:46Z 置信度 0.70
• Source code 2. qPCR 14-miRNA neural network source code.
  crossref 2017-11-03T07:01:58Z 置信度 0.70
• Figure 6: Evaluation metrics for artificial neural network (ML-EdgeIIoTset).
  crossref 2024-08-28T01:48:06Z 置信度 0.70
• Table 8: Distribution of neural network types and their percentages.
  crossref 2026-04-27T08:09:01Z 置信度 0.70
• Feasibility of an interpretability metric for LIDAR data
  The use of LIDAR (Light Imaging, Detection and Ranging) data for detailed terrain mapping and object recognition is becoming increasingly common. While the rendering of LIDAR imagery is expressive, there is a need for a comprehensive performance metric that pr…
  crossref Ye Duan, John M. Irvine, Hua-Mei Chen, Genshe Chen 等 2018-05-14T21:47:47Z 置信度 0.70
• Exploiting network redundancy for low-cost neural network realizations
  A method is presented to optimize a trained neural network for physical realization styles. Target architectures are embedded microcontrollers or standard cell based ASIC designs. The approach exploits the redundancy in the network, required for successful tra…
  crossref H. Keegstra, W.J. Jansen, J.A.G. Nijhuis, L. Spaanenburg 等 2002-12-23T20:16:22Z 置信度 0.70
• Multivariate Fuzzy Perturbed Neural Network Approximations
  crossref George A. Anastassiou 2015-06-23T09:56:55Z 置信度 0.70
• Vehicle types classification using deep neural network techniques
  Traf􀅭ic 􀅭low is one of the most important information elements in intelligent traf􀅭ic transportation engineering.This study developed a vehicle type classi􀅭ication system using a neural network technique.The architecture of this study is divided into two p…
  crossref 2018-02-21T05:03:03Z 置信度 0.70
• Self-organized feature maps and information theory
  We describe new algorithms for self-organizing feature maps based on a generalized information theory. In our model the maximizing of the local information transfer leads to a topologically ordered map whereas the increase of global information fails. The adap…
  crossref Klaus Holthausen, Olaf Breidbach 2002-08-25T02:35:54Z 置信度 0.70
• Graph Neural Network for Online Payment Fraud Detection
  crossref Yu Xie, Yue Tian, Jiamin Yao, Guanjun Liu 2026-05-15T14:28:02Z 置信度 0.70
• Fixed-Sign Binary Neural Network: An Efficient Design of Neural Network for Internet-of-Things Devices
  High computational requirement and rigorous memory cost are the significant issues which limit Convolutional Neural Networks' deployability in resource-constrained environments typically found in edge devices of Internet-of-Things (IoT). To address the problem…
  crossref Yang Li, Yuanyuan Bao, Wai Chen 2020-09-09T20:16:47Z 置信度 0.70
• Improving the Interpretability of Artificial Neural Networks Using the Example of the Pricing Options Problems
  Abstract In this paper, we demonstrate how to improve the interpretability of neural networks using standard problems of computational finance as an example. In our first approach, we justify that a feedforward neural network with one hidden layer and positive…
  crossref O. E. Kudryavtsev, D. V. Postolova 2025-03-24T08:37:16Z 置信度 0.70
• Image segmentation using multilayer neural network
  An image segmentation method based on multilayer neural networks is introduced. This method was applied to both the aerial and texture images. The performance of this method on a synthetic image is compared to a model based image segmentation technique. Simula…
  crossref H.A. Malki 2003-01-02T16:19:33Z 置信度 0.70
• Brainchild: a fault tolerant neural network
  Summary form only given, as follows. Brainchild is a neural network designed to bridge the gap between current neural models and the brain. It models the physical organization of neurons by using both feedforward and lateral connections. It also has a high deg…
  crossref E. Kidwell 2003-01-13T18:46:33Z 置信度 0.70
• Modeling segmentation of a visual scene via neural oscillators: fragmentation, discovery of details and attention
  The present study analyses the problem of binding and segmentation of a visual scene by means of a network of neural oscillators, laying emphasis on the problems of fragmentation, perception of details at different scales and spatial attention. The work is bas…
  crossref Mauro Ursino, Giuseppe-Emiliano La Cara 2004-04-05T10:37:13Z 置信度 0.70