类脑计算 · 全部实体（第 11 / 100 页）

本页收录第 1001–1100 条，共 10000 条 · 返回 类脑计算 首页

• Flood Prediction by using Artificial Neural Network: A Case Study in Temerloh, Pahang
  Floods are natural disasters that can cause significant property damage and sometimes result in loss of life. In Malaysia, floods occur every year, particularly on the East Coast of Peninsular Malaysia, due to the Northeast Monsoon and the impacts of climate c…
  crossref Ahmad Jazli Abdul Rahman, Nor Azuana Ramli 2024-11-17T22:17:44Z 置信度 0.70
• Decision letter for "Neural Determinants of Sedentary Lifestyle in Older Adults: A Brain Network Analysis"
  crossref 2025-01-09T16:04:23Z 置信度 0.70
• Prediction Model For Digital Image Tampering Using Customized Deep Neural Network Techniques
  Abstract Image tampering detection is a critical area of research, given the widespread use of manipulated images for deceptive purposes. Convolutional Neural Networks (CNNs) have shown significant potential in automating the identification of tampered images.…
  crossref Sachin Saxena, Archana Singh, Shailesh Tiwari 2024-06-13T19:32:25Z 置信度 0.70
• NERD: Neural Network for Edict of Risky Data Streams
  Cyber incidents can have a wide range of cause from a simple connection loss to an insistent attack. Once a potential cyber security incidents and system failures have been identified, deciding how to proceed is often complex. Especially, if the real cause is …
  crossref Peter Hillmann, Sandro Passarelli, Cem Gündogan, Lars Stiemert 等 2024-06-21T09:30:04Z 置信度 0.70
• Neural Network Controller for Hybrid Energy Management System Applied to Electric Vehicles
  crossref Alex do Nascimento Ribeiro, Daniel Mauricio Muñoz 2024-07-11T12:18:56Z 置信度 0.70
• Front Matter: Volume 13652
  crossref 2025-06-11T23:42:46Z 置信度 0.70
• Recommendation: Quantitative analysis of lateral root development with time-lapse imaging and deep neural network — R1/PR9
  crossref 2024-02-13T03:07:40Z 置信度 0.70
• Reviewer #3 (Public Review): Hippocampome.org v2.0: a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits
  crossref 2024-01-26T06:25:53Z 置信度 0.70
• A novel approach for Plant disease Classification through Neural Network-Based Color Feature Analysis
  Abstract plant disease identification using machine vision, which is a challenge in terms of maximizing both the quality and quantity of plant growth. The infection makes plants susceptible to disease. This needs continuous monitoring by experts, which is proh…
  crossref Archana KS, Arun S 2024-10-14T05:25:26Z 置信度 0.70
• Review for "Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms"
  crossref 2025-01-25T16:09:21Z 置信度 0.70
• Real-Time spike sorting using an optimized STDP Spiking Neural Network on FPGA
  crossref Jérémy Cheslet, Marie Bernert, Romain Beaubois, Blaise Yvert 等 2024-09-09T17:35:05Z 置信度 0.70
• Multimodal Fusion for Abusive Speech Detection Using Liquid Neural Networks and Convolution Neural Network
  crossref Ks Paval, Vishnu Radhakrishnan, Km Krishnan, G Jyothish Lal 等 2024-11-04T23:06:46Z 置信度 0.70
• Deep Neural Network-Aided Radio Frequency Fingerprinting for Identification of Near Field Communication Tags
  crossref Woongsup Lee, Seon Yeob Baek 2024-10-21T21:37:49Z 置信度 0.70
• Forecasting precious metals price based on artificial neural network trained by Lévy flight optimization algorithm
  Artificial neural networks are popular data-driven models extensively used for predicting the prices of precious metals. This study suggests an optimized artificial neural network model specifically designed for monthly price of precious metals forecasting. Fo…
  crossref Farshid Mehrdoust, Maryam Noorani 2024-03-11T11:54:55Z 置信度 0.70
• Reinforcement learning (RL)-based semantic segmentation and attention based backpropagation convolutional neural network (ABB-CNN) for breast cancer identification and classification using mammogram images
  crossref Neha Thakur, Pardeep Kumar, Amit Kumar 2024-05-11T13:01:47Z 置信度 0.70
• Efficient Automation of Neural Network Design: A Survey on Differentiable Neural Architecture Search
  In the past few years, Differentiable Neural Architecture Search (DNAS) rapidly imposed itself as the trending approach to automate the discovery of deep neural network architectures. This rise is mainly due to the popularity of DARTS (Differentiable ARchitecT…
  crossref Alexandre Heuillet, Ahmad Nasser, Hichem Arioui, Hedi Tabia 2024-05-15T11:33:30Z 置信度 0.70
• UTDNet: A unified triplet decoder network for multimodal salient object detection
  crossref Fushuo Huo, Ziming Liu, Jingcai Guo, Wenchao Xu 等 2023-11-24T11:44:51Z 置信度 0.70
• Neural Touch for Enhanced Wearable Haptics with Recurrent Neural Network and IoT-Enabled Tactile Experiences
  crossref K. Radhakrishna, D. Satyaraj, Hanumaji Kantari, V. Srividhya 等 2024-05-06T13:20:54Z 置信度 0.70
• A Prediction Model for Air Pollution using Artificial Neural Network and Multiple Linear Regression
  Abstract O ver the past few decades, air pollution and preventive measures have proven scientifically challenging and the issue is still unending on a worldwide scale. The number of contaminants in the air is increasing daily as a result of the expanding popul…
  crossref Lokesh Kumar, Gaurav Kumar 2024-02-22T10:22:49Z 置信度 0.70
• Neural Network Architectures
  crossref Gerald Friedland 2023-12-01T06:04:04Z 置信度 0.70
• Decision letter for "Optimizing Satellite-Based Latent Heating Rate Profiling Using a Convolutional Neural Network Heating (CNNH) Algorithm"
  crossref 2025-10-21T22:51:12Z 置信度 0.70
• Investigating attention manipulation in behavioural data using Hierarchical Gaussian Filter and neural network models
  Attention is a critical cognitive process that has been hypothesized to enable the brain to selectivelyfocus on relevant stimuli while filtering out distractions, thereby optimizing the allocation of limitedcomputational resources. Within the predictive coding…
  crossref Abdullah Al Saqib Majumder 2024-11-09T18:22:48Z 置信度 0.70
• Neural Network-Based Traffic Control System
  Effective traffic management is essential for modern cities, as it helps to alleviate congestion and enhance mobility. This research proposes a novel approach to predicting traffic flow, utilizing a combination of advanced deep learning techniques. The model i…
  crossref Gauri V. Sonawane 2025-01-21T10:17:48Z 置信度 0.70
• A Convolutional Neural Network-Based Method for Accurate Computation of Scattered Fields From Reconfigurable Intelligent Surfaces
  The cell-to-cell coupling in a reconfigurable intelligent surface (RIS) is very different from a periodic structure, where coupling effects can be precisely evaluated via full-wave analysis with periodic boundary conditions. We propose a novel method based on …
  crossref Yuanzhi Liu, Costas Sarris 2024-12-23T09:44:07Z 置信度 0.70
• Review for "A PNP ion channel deep learning solver with local neural network and finite element input data"
  crossref 2024-09-24T17:15:02Z 置信度 0.70
• Broken Tooth Gear Fault Detection Using Vibration Signals Based on Convolutional Neural Network
  Abstract Gear faults are a major concern in industrial settings, leading to performance degradation and potential system failures. This paper explores the use of Convolutional Neural Networks (CNNs) for broken tooth fault detection in gear systems. Traditional…
  crossref Priyom Goswami, Rajiv Nandan Rai 2024-09-24T14:01:44Z 置信度 0.70
• A Multiple Transferable Neural Network Method with Domain Decomposition for Elliptic Interface Problems
  crossref Tianzheng Lu, Lili Ju, Liyong Zhu 2024-08-27T23:19:03Z 置信度 0.70
• Automatic Modulation Classification Using Convolutional Neural Network and Support Vector Machine
  crossref Shanza Nasir, Shahzad Amin Sheikh, fahad mumtaz malik 2024-08-28T22:17:42Z 置信度 0.70
• Research of improvement of multilingual scientific translation model based on neural network attention mechanism
  crossref jing zhao, hongjing chang, Xuguang Zhang, chunmao li 2024-11-08T16:12:17Z 置信度 0.70
• Enhancing Speaker Diarization with Deep Neural Network Embeddings and Spectral Clustering
  crossref Yaqian Li, Xiaolong Zhang, Haibin Li, Wengming Zhang 2024-03-20T18:58:51Z 置信度 0.70
• A Comparative Study of Machine Learning and Neural Network Models in Short-term Market Prediction
  Abstract The prediction of the stock market and the prices of other commodities like crude oil, 1 constitutes a challenging task. Recently, the rapid progress in the field of Machine Leaning (ML), 2 led to an increased interest in applying ML techniques to mar…
  crossref Fayez Abu-Ajamieh 2024-06-21T18:06:58Z 置信度 0.70
• Automatic Grading of Barley Grain for Brewery Industries Using Convolutional Neural Network
  crossref Debalke Embeyale, Yao-Tien Chen, Yaregal Assabie 2024-12-19T18:38:06Z 置信度 0.70
• Practical application of quantum neural network to materials informatics
  Abstract Quantum neural network (QNN) models have received increasing attention owing to their strong expressibility and resistance to overfitting. It is particularly useful when the size of the training data is small, making it a good fit for materials inform…
  crossref Hirotoshi Hirai 2024-04-13T02:01:55Z 置信度 0.70
• DCDLN: A densely connected convolutional dynamic learning network for malaria disease diagnosis
  crossref Zhijun Zhang, Cheng Ding, Mingyang Zhang, YaMei Luo 等 2024-04-29T15:40:14Z 置信度 0.70
• SJFO: Sail Jelly Fish Optimization enabled VM migration with DRNN-based prediction for load balancing in cloud computing
  crossref Rajesh Rathinam, Premkumar Sivakumar, Sivakumar Sigamani, Ishwarya Kothandaraman 2024-06-03T14:44:39Z 置信度 0.70
• Chicken moth flame optimization and region-based convolution neural network for water quality prediction
  crossref D. Justin Jose, C. Helen Sulochana 2024-12-19T08:37:22Z 置信度 0.70
• Research on the Application of Chemical Process Fault Diagnosis Methods Based on Neural Network
  crossref Kongpeng Wei, Hongbin Gu, Xiaolong Li, Bo Liu 2024-07-30T18:34:42Z 置信度 0.70
• Research and Application of E-commerce Marketing Fraud Detection Method Based on Graph Neural Network
  crossref Hui Zhu, Weijie Zhong, Zihao Huang, Zhenyu Wang 2025-03-07T06:34:31Z 置信度 0.70
• Blindly separated spontaneous network-level oscillations predict corticospinal excitability
  Abstract Objective. The corticospinal responses of the motor network to transcranial magnetic stimulation (TMS) are highly variable. While often regarded as noise, this variability provides a way of probing dynamic brain states related to excitability. We aime…
  crossref Maria Ermolova, Johanna Metsomaa, Paolo Belardinelli, Christoph Zrenner 等 2024-06-04T22:28:25Z 置信度 0.70
• Deep graph convolutional neural network for one-dimensional hepatic vascular haemodynamic prediction
  Abstract Hepatic vascular hemodynamics is an important reference indicator in the diagnosis and treatment of hepatic diseases. However, Method based on Computational Fluid Dynamics(CFD) are difficult to promote in clinical applications due to their computation…
  crossref Weiqng Zhang, Shuaifeng Shi, Quan Qi 2024-08-16T21:35:14Z 置信度 0.70
• Enhancing biomedical knowledge discovery through hybrid text-mining and graph neural network approaches in ANDSystem
  crossref 2024-09-25T13:20:38Z 置信度 0.70
• Optimal Li-Ion Battery Charging with a Hybrid Model Based on Physical Modeling and a Neural Network
  crossref Milad Nouri 2024-01-22T23:07:46Z 置信度 0.70
• Copula Tubular Quantum Based Spearman Deep Neural for Influential Node Tracing in Social Network
  Abstract Social networks are one the foremost origins of information transmission at present. Nevertheless, not all nodes in social networks are indistinguishable. As a matter of fact, certain nodes are said to be more influential than others, or to be more sp…
  crossref Vimalkumar P, Balasubramanian C 2024-02-19T18:21:10Z 置信度 0.70
• PEGSGraph: a Graph Neural Network for fast earthquake characterization based on Prompt ElastoGravity Signals
  State-of-the-art earthquake early warning systems use the early records of seismic waves to estimate the magnitude and location of the seismic source before the shaking and the tsunami strike. Because of the inherent properties of early seismic records, those …
  crossref Céline Hourcade, Kévin Juhel, Quentin Bletery 2024-07-26T17:06:40Z 置信度 0.70
• Precise estimation of activation energies in gas-phase chemical reactions via artificial neural network
  Various machine learning (ML) models are presented in this study, aiming to forecast the barrier heights (BHs) of gas-phase chemical reactions. The input features utilized in six distinct models were obtained from the structural and thermodynamic attributes of…
  crossref Guo-Jin Cao, Sheng-Jie Lu 2024-07-30T00:54:01Z 置信度 0.70
• Graph neural network for 3-dimensional structures including dihedral angles for molecular property prediction
  The prediction of molecular properties using graph neural network (GNN) based approaches has attracted great attention in recent years. Topological molecular graphs are commonly used for representing molecules in machine learning (ML). However, the challenge i…
  crossref Sri Abhirath Reddy Sangala, Shampa Raghunathan 2024-11-13T07:34:42Z 置信度 0.70
• Review for "Diagnosis of glaucoma using multi‐scale attention block in convolution neural network and data augmentation techniques"
  crossref 2024-03-13T17:19:47Z 置信度 0.70
• Multi-Patch Isogeometric Convolution Hierarchical Deep-Learning Neural Network
  crossref Lei Zhang, Chanwook Park, Thomas J.R. Hughes, Wing Kam Liu 2024-07-24T08:51:34Z 置信度 0.70
• Neural Network Architecture of Embodied Intelligence
  In recent years, advances in artificial intelligence (AI) and machine learning have been driven by advances in the development of large language models (LLMs) based on deep neural networks. At the same time, despite its substantial capabilities, LLMs have fund…
  crossref Ayrat Rafkatovich Nurutdinov 2025-06-05T10:16:56Z 置信度 0.70
• Neural Network Model for Detecting Leaf Diseases and Assessing Invasive Species: Computational Approach
  Invasive species and plant diseases are critical threats to ecosystems and agriculture worldwide. Effective early detection of these threats can significantly mitigate their impact on biodiversity and crop yields. This paper presents a neural network-based mod…
  crossref MD Nahidul Sabit 2024-10-25T00:41:13Z 置信度 0.70
• Fuzzy-Based Convolutional Neural Network Model for Structural Response Prediction Under Seismic Excitation
  This study addresses the challenge of predicting the dynamic behavior of the structures under seismic excitation. Accurate prediction of such systems' responses is critical for the design and evaluation of buildings and infrastructure. Traditional met…
  crossref Mohammad Sadegh Barkhordari, Mohammad Mahdi Barkhordari 2024-10-15T01:23:56Z 置信度 0.70
• Reinforcement learning-based autonomous attacker to uncover computer network vulnerabilities
  crossref Ahmed Mohamed Ahmed, Thanh Thi Nguyen, Mohamed Abdelrazek, Sunil Aryal 2024-05-07T05:02:31Z 置信度 0.70
• Memristor-Based Conditioned Inhibition Neural Network Circuit With Blocking Generalization and Differentiation
  crossref Junwei Sun, Peilong Gao, Shiping Wen, Peng Liu 等 2023-11-09T19:03:51Z 置信度 0.70
• Evolutionary Reinforcement Learning of Neural Network Controller for Acrobot Task — Part4: Particle Swarm Optimization
  Evolutionary algorithms and swarm intelligence algorithms find applicability in reinforcement learning of neural networks due to their independence from gradient-based methods. To achieve successful training of neural networks using these algorithms, careful c…
  crossref Hidehiko Okada 2024-03-06T02:50:00Z 置信度 0.70
• Derivative-enhanced Deep Operator Network
  crossref Yuan Qiu, Nolan Bridges, Peng Chen 2025-11-03T11:20:56Z 置信度 0.70
• A Convolutional Neural Network-Based Method for Accurate Computation of Scattered Fields From Reconfigurable Intelligent Surfaces
  The cell-to-cell coupling in a reconfigurable intelligent surface (RIS) is very different from a periodic structure, where coupling effects can be precisely evaluated via full-wave analysis with periodic boundary conditions. We propose a novel method based on …
  crossref Yuanzhi Liu, Costas Sarris 2024-04-08T13:45:17Z 置信度 0.70
• Retraction Note: Alcoholism identification via convolutional neural network based on parametric ReLU, dropout, and batch normalization
  crossref Shui-Hua Wang, Khan Muhammad, Jin Hong, Arun Kumar Sangaiah 等 2024-04-24T00:01:51Z 置信度 0.70
• ViTBayesianNet: An adaptive deep bayesian network-aided alzheimer disease detection framework with vision transformer-based residual densenet for feature extraction using MRI images
  crossref Revathi Mohan, Rajesh Arunachalam, Neha Verma, Shital Mali 2024-12-12T00:14:36Z 置信度 0.70
• Retraction Note: Applications of artificial intelligence and hybrid neural network methods with new bonding method to prevent electroshock risk and insulation faults in high-voltage underground cable lines
  crossref Bahadır Akbal 2024-05-21T00:01:28Z 置信度 0.70
• Optimization of Convolutional Neural Network hyperparameters using Genetic Algorithms
  The ever-increasing complexity of deep learning models leads to larger sizes and computational costs (greater execution time), making models extremely difficult to implement in resource constrained environments. Moreover, extensive hyperparameter tuning is nec…
  crossref Nirmit Shah 2025-07-10T17:50:00Z 置信度 0.70
• Review for "Fault estimation for multi-rate descriptor systems using bi-directional long short-term memory neural network"
  crossref 2025-10-22T01:09:11Z 置信度 0.70
• Neural Network Compression Using Binarization and Few Full-Precision Weights
  Quantization and pruning are two effective Deep Neural Networks model compression methods.In this paper, we propose Automatic Prune Binarization (APB), a novel compression technique combining quantization with pruning. APB enhances the representational capabil…
  crossref Cosimo Rulli, Franco Maria Nardini, Salvatore Trani, Rossano Venturini 2024-08-19T05:54:18Z 置信度 0.70
• The Bézier curve and neural network model of the time-domain transient signals
  The discussion is for the memory of Oleg Alexandrovich Tretyakov. In the discussion, one characteristic of the signal transfer of Professor Tretyakov's Evolutionary Approach to the Electromagnetics method is presented. Theoretically, the problem of the signal …
  crossref Emre Eroglu 2024-05-28T03:08:47Z 置信度 0.70
• Few-Shot Relation Extraction With Dual Graph Neural Network Interaction
  crossref Jing Li, Shanshan Feng, Billy Chiu 2023-06-02T19:52:48Z 置信度 0.70
• Pathological brain classification using multiple kernel-based deep convolutional neural network
  crossref Lingraj Dora, Sanjay Agrawal, Rutuparna Panda, Ram Bilas Pachori 2023-10-03T09:02:49Z 置信度 0.70
• A Random Focusing Method with Jensen–Shannon Divergence for Improving Deep Neural Network Performance Ensuring Architecture Consistency
  Abstract Multiple hidden layers in deep neural networks perform non-linear transformations, enabling the extraction of meaningful features and the identification of relationships between input and output data. However, the gap between the training and real-wor…
  crossref Wonjik Kim 2024-06-17T19:02:15Z 置信度 0.70
• Review for "Development of a deep neural network and empirical model for predicting local gas holdup profiles in bubble columns"
  crossref 2025-10-22T01:07:19Z 置信度 0.70
• Phonetic discrimination experiments with a spatiotemporal recognition network
  crossref 2003-04-25T05:05:53Z 置信度 0.70
• LEP — A Neural Model learning Reliably
  crossref Jian- Kang Wu 2013-12-08T22:06:39Z 置信度 0.70
• A virtual network for reorganizable neural architectures
  crossref Wong, Lursinsap 2003-01-13T13:46:33Z 置信度 0.70
• A neural network for 3-satisfiability problems
  crossref Chen, Hsieh 2003-01-13T18:46:33Z 置信度 0.70
• State estimation for memristor-based neural networks with time-varying delays
  crossref Hongzhi Wei, Ruoxia Li, Chunrong Chen 2014-05-03T08:58:02Z 置信度 0.70
• Impulsive controller design for exponential synchronization of delayed stochastic memristor-based recurrent neural networks
  crossref A. Chandrasekar, R. Rakkiyappan 2015-09-11T17:41:55Z 置信度 0.70
• A plethora of behaviors in a memristor based Hopfield neural networks (HNNs)
  crossref Z. T. Njitacke, J. Kengne, H. B. Fotsin 2018-05-03T04:49:08Z 置信度 0.70
• Research on Early Warning Model of Credit Risk Transmission of Enterprise Group Based on Graph Neural Network and Knowledge Graph
  crossref 2026-05-25T08:46:27Z 置信度 0.70
• Effect of neural firing pattern on NbOx/Al2O3 memristor-based reservoir computing system
  The implementation of reservoir computing using resistive random-access memory as a physical reservoir has attracted attention due to its low training cost and high energy efficiency during parallel data processing. In this work, a NbOx/Al2O3-based memristor d…
  crossref Dongyeol Ju, Hyeonseung Ji, Jungwoo Lee, Sungjun Kim 2024-07-23T15:52:57Z 置信度 0.70
• Neural networks based on in-sensor computing of optoelectronic memristor
  crossref Zhang Zhang, Qifan Wang, Gang Shi, Yongbo Ma 等 2024-05-08T16:17:33Z 置信度 0.70
• The Ouroboros of Memristors: Neural Networks Facilitating Memristor Programming
  crossref Zhenming Yu, Ming-Jay Yang, Jan Finkbeiner, Sebastian Siegel 等 2024-07-19T13:30:48Z 置信度 0.70
• Neural network algorithms for motion stereo
  crossref Zhou, Chellappa 2003-01-13T13:46:33Z 置信度 0.70
• Unsupervised learning in the N-dimensional Coulomb network
  crossref 2003-04-25T05:05:53Z 置信度 0.70
• The H1 neural network trigger
  crossref C. Kiesling 2004-03-02T02:26:50Z 置信度 0.70
• Network generalization differences quantified
  crossref Derek Partridge 2002-07-25T12:59:42Z 置信度 0.70
• The extended piecewise quadratic neural network
  crossref David M. Weber, David P. Casasent 2002-07-25T22:54:47Z 置信度 0.70
• DEFAnet—A deterministic neural network concept for function approximation
  crossref Wolfgang J. Daunicht 2003-04-25T01:05:53Z 置信度 0.70
• Informational characteristics of neural networks capable of associative learning based on Hebbian plasticity
  crossref A A Frolov, I P Murav'ev 2015-08-18T20:04:23Z 置信度 0.70
• Automated Generation of SPICE Models of Memristor-Based Neural Networks from Python Models
  crossref Daniil Nikishov, Alexander Antonov 2023-06-05T17:43:26Z 置信度 0.70
• Divergence measures based on entropy families: a tool for guiding the growth of neural networks
  crossref H Andree, A Lodder, A Taal 2002-08-25T02:35:54Z 置信度 0.70
• The Patch algorithm: fast design of binary feedforward neural networks
  crossref G T Barkema, H M A Andree, A Taal 2015-08-18T20:04:17Z 置信度 0.70
• Advancing interconnect density for spiking neural network hardware implementations using traffic-aware adaptive network-on-chip routers
  crossref Snaider Carrillo, Jim Harkin, Liam McDaid, Sandeep Pande 等 2012-04-23T23:10:49Z 置信度 0.70
• Figure 9: Evaluation metrics for artificial neural network (DNN-EdgeIIoTset).
  crossref 2024-08-28T01:48:06Z 置信度 0.70
• Source code 3. qPCR 7-miRNA neural network source code.
  crossref 2017-11-03T11:01:58Z 置信度 0.70
• Leverage graph neural network for molecular properties prediction
  During the age of deep learning technologies, which have exhibited significant potential in reducing costs and expediting medical development, predicting molecular properties has become a prevalent task that capitalizes on the capabilities of deep learning. Th…
  crossref Kamol Punnachaiya 2023-09-15T06:01:19Z 置信度 0.70
• Fig. 2. Images (a, b) generated by the neural network.
  crossref 2022-10-17T06:41:35Z 置信度 0.70
• Figure 10: (A) Neural network training phase (B) Validation epochs.
  crossref 2026-01-27T08:54:27Z 置信度 0.70
• Figure 2: Framework of the proposed dual branch neural network.
  crossref 2022-11-14T03:16:13Z 置信度 0.70
• Front Matter
  crossref 2011-10-06T10:14:16Z 置信度 0.70
• Low-rank network models of neural computations
  Réseaux de neurones de bas rang et calculs neuronaux À tout instant, des myriades de neurones coopèrent au sein d’un système nerveux, produisant des motifs d’activité collectifs qui forment un substrat biologique pour la perception, la cognition, et le comport…
  crossref Adrian Valente 2026-04-07T08:08:14Z 置信度 0.70
• A neural network model for real-time adaptive clustering
  crossref L. Fu 2002-12-30T22:49:31Z 置信度 0.70
• A Neural Network for Motion Processing
  crossref Y.T. ZHOU, R. CHELLAPPA 2014-07-01T11:42:25Z 置信度 0.70
• The Modified Probabilistic Neural Network
  crossref 2012-07-18T16:55:18Z 置信度 0.70