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• StrategicVideoRec: A Strategic Approach for Scientific Video Recommendation Integrating BERT and Fact Driven Semantics
  crossref M. Prathibha, Gerard Deepak 2025-05-26T03:04:09Z 置信度 0.70
• Digital Innovation in Tourism: Exploring the Potential of Chatbots
  crossref Isabel Lopes, Teresa Guarda, Pedro Oliveira, Paula Odete Fernandes 2025-05-28T09:29:48Z 置信度 0.70
• Smart Technologies System Implementation Using a Case Study in the South African Library Education Sector
  crossref Oluwasegun Julius Aroba, Michael Rudolph 2025-05-28T09:29:58Z 置信度 0.70
• Breast Cancer Identification Using Improved DarkNet53 Model
  crossref Noor Ul Huda Shah, Rabbia Mahum, Dur e Maknoon Nisar, Noor Ul Aman 等 2023-03-27T19:03:17Z 置信度 0.70
• Embryonics and Immunotronics: Biologically Inspired Computer Science Systems
  crossref A. Tyrrell 2013-02-06T05:08:10Z 置信度 0.70
• Bio-inspired computing and applications (LSMS-ICSEE, 2010)
  crossref Kang Li, Xia Hong, Guido Maione, Qun Niu 2012-06-06T02:57:58Z 置信度 0.70
• Systems biology markup language for cancer system
  crossref Suryasarathi Barat, Avishek Das, Durjoy Majumder 2010-01-26T17:36:43Z 置信度 0.70
• DCS Applications
  crossref Aziz Ouaarab 2020-03-24T13:02:55Z 置信度 0.70
• EasyOnto: A Collaborative Semiformal Ontology Development Platform
  crossref Usha Yadav, B. K. Murthy, Gagandeep Singh Narula, Neelam Duhan 等 2017-10-04T08:25:22Z 置信度 0.70
• A Survey of Cross-Layer Design for Wireless Visual Sensor Networks
  crossref Afaf Mosaif, Said Rakrak 2018-03-09T11:43:48Z 置信度 0.70
• Solving with Bees
  crossref 2024-12-01T08:28:09Z 置信度 0.70
• The Neural Engineering Framework (NEF)
  crossref Elishai Ezra Tsur 2021-07-19T12:30:34Z 置信度 0.70
• Advances on Brain Inspired Computing
  crossref Stefano Squartini, Sanqing Hu, Qingshan Liu 2013-03-21T00:12:30Z 置信度 0.70
• Bio-Inspired Computing Architectures: The Embryonics Approach
  crossref G. Tempesti, D. Mange, A. Stauffer 2006-10-11T16:54:11Z 置信度 0.70
• Smart Classroom Roll Caller System with IOT Architecture
  crossref Ching Hisang Chang 2012-01-06T16:44:03Z 置信度 0.70
• Neuromorphic Computing Systems with Emerging Devices
  crossref Qiumeng Wei, Jianshi Tang, Bin Gao, Xinyi Li 等 2021-12-17T21:34:07Z 置信度 0.70
• A Novel Approach for Malicious Node Detection in MANET
  crossref K. P. Anjana, K. G. Preetha 2015-12-14T01:02:33Z 置信度 0.70
• Enhanced Throughput and Accelerated Detection of Network Attacks Using a Membrane Computing Model Implemented on a GPU
  crossref Rufai Kazeem Idowu, Ravie Chandren Muniyandi 2018-08-29T18:31:42Z 置信度 0.70
• Nature Inspired Algorithms for Load Balancing in Cloud Computing
  crossref Sebagenzi Jason, Suchithra R. 2017-02-15T12:42:06Z 置信度 0.70
• Bio-Inspired Visual Navigation System for Insectsized Flying Robots
  crossref Weixin Xiong 2026-01-28T20:54:45Z 置信度 0.70
• Fast Implementation of a Bio-inspired Model for Decentralized Gathering
  crossref Bernard Girau, Cesar Torres-Huitzel 2009-01-14T18:57:00Z 置信度 0.70
• Spatiotemporal Enhanced Joint Optimization for Spike Camera Based 3D Reconstruction
  crossref Binqiang Wang 2026-01-27T04:49:35Z 置信度 0.70
• Sentiment Analysis of Online Product Reviews Using CNN-LSTM Cascaded Deep Learning Architecture
  crossref Ancy Rominus, Chinju John, Jayakrushna Sahoo 2025-05-26T03:04:03Z 置信度 0.70
• Connecting Probabilistic Databases to Quantum Computing and Tensor Networks via Graphical Models
  crossref Valter Uotila 2026-07-04T10:29:31Z 置信度 0.70
• Advanced Techniques to Enhance Human Visual Ability – A Review
  crossref A. Vani, M. N. Mamatha 2020-01-06T15:02:40Z 置信度 0.70
• Concluding Remarks at the Beginning of a New Computing ERA
  crossref Varun Bhojwani, Stephen Chu, Mary Mehrnoosh Eshaghian‐Wilner, Shawn Singh 等 2009-11-24T16:16:40Z 置信度 0.70
• Prediction of scouring around an arch-shaped bed sill using Neuro-Fuzzy model
  crossref Alireza Keshavarzi, Reza Gazni, Seyed Rahman Homayoon 2011-08-23T00:38:17Z 置信度 0.70
• Generalized Skin Cancer Image Classification Performance Using Xception Model
  crossref Qurban A. Memon, Ghaya Al Ameri, Namya Musthafa, Aryam AlShamsi 等 2025-05-26T03:04:22Z 置信度 0.70
• Machine Learning-Based Multimodal Depression Diagnosis for IT Personnel Using CCTV and Messaging Streams
  crossref B. Manjulatha, Suresh Pabboju 2025-06-05T06:07:29Z 置信度 0.70
• Area Efficient Lightweight Cipher System Implementation for Edge Device
  crossref Aditi Kumari, Ankita Mondal, Aditi Kumari, Tribeni Prasad Banerjee 2025-05-28T09:30:43Z 置信度 0.70
• Designing Green Routing and Scheduling for Home Health Care
  crossref Hossein Shokri Garjan, Alireza Abbaszadeh Molaei, Fariba Goodarzian, Ajith Abraham 2022-02-21T17:09:04Z 置信度 0.70
• Bio-inspired Error Detection for Complex Systems
  crossref Martin Drozda, Iain Bate, Jon Timmis 2012-01-30T21:48:07Z 置信度 0.70
• Palindromic completion of a word
  crossref Kalpana Mahalingam, K.G. Subramanian 2010-12-09T10:33:18Z 置信度 0.70
• Multiattribute Methodologies in Financial Decision Aid
  This chapter introduces the capability of the numerical multi-dimensional approach to solve complex problems in finance. It is well known how, with the growth of computational resource, scientists have developed numerical algorithms for the resolution of compl…
  crossref M. Ciprian, M. Kaucic 2011-05-24T13:17:52Z 置信度 0.70
• Survey of Image Processing Techniques in Medical Image Assessment Methodologies
  crossref Anandakumar Haldorai, Arulmurugan Ramu 2021-06-14T05:02:45Z 置信度 0.70
• An Interior Point–Inspired Algorithm for Linear Programs Arising in Discrete Optimal Transport
  Discrete optimal transport problems give rise to very large linear programs (LPs) with a particular structure of the constraint matrix. In this paper, we present a hybrid algorithm that mixes an interior point method (IPM) and column generation, specialized fo…
  crossref Filippo Zanetti, Jacek Gondzio 2023-05-12T12:50:40Z 置信度 0.70
• Enhancing Assistive Technologies With Neuromorphic Computing
  The development of intelligent neuroprosthetics, which promise to augment human brain function is vital for augmentative assistive technologies. Neuromorphic sensors and processors are particularly adept at mimicking the brain's efficient sensory processing, o…
  crossref G. V. S. Anil Chandra, Bhanuprakash Ananthakumar, Ramya Raghavan 2024-11-29T15:16:27Z 置信度 0.70
• Review for "Dynamic attention signaling in V4: relation to fast‐spiking/non‐fast‐spiking cell class and population coupling"
  crossref 2023-02-06T09:03:47Z 置信度 0.70
• Review for "ProDCoNN: Protein design using a convolutional neural network"
  crossref 2020-01-15T15:06:10Z 置信度 0.70
• Review for "RobMedNAS: searching robust neural network architectures for medical image synthesis"
  crossref 2024-08-14T17:14:57Z 置信度 0.70
• A Review on Neural Network Methodology for Diagnosis of Kidney Stone
  crossref 2016-04-28T11:43:26Z 置信度 0.70
• Review for "ProDCoNN: Protein design using a convolutional neural network"
  crossref 2020-01-15T15:06:10Z 置信度 0.70
• Plasticity in adult sensory cortex: a review
  crossref Aniruddha Das 2002-08-25T02:35:54Z 置信度 0.70
• Review for "Artificial neural network encoding of molecular wavefunctions for quantum computing"
  crossref 2024-09-27T00:04:51Z 置信度 0.70
• A Review of Power System Fault Diagnosis with Spiking Neural P Systems
  With the advancement of technologies it is becoming imperative to have a stable, secure and uninterrupted supply of power to electronic systems as well as to ensure the identification of faults occurring in these systems quickly and efficiently in case of any …
  crossref Yicen Liu, Ying Chen, Prithwineel Paul, Songhai Fan 等 2021-05-12T10:59:12Z 置信度 0.70
• Review for "An electricity price interval forecasting by using residual neural network"
  crossref 2020-06-16T17:05:22Z 置信度 0.70
• Review for "Recognizing schizophrenia using facial expressions based on convolutional neural network"
  crossref 2023-04-18T17:02:58Z 置信度 0.70
• Condor: A Neural Connection Network for Enhanced Attention
  Abstract The attention mechanism in traditional neural networks relies on pairwise interactions between tokens, limiting its ability to capture complex, multi-token relationships. This study introduces Condor, a novel architecture that extends the attention me…
  crossref Youngseong Kim 2025-08-27T03:48:06Z 置信度 0.70
• Review: Provable Observation Noise Robustness for Neural Network Control Systems — R0/PR3
  crossref 2024-02-13T06:55:14Z 置信度 0.70
• A Subsampling Based Neural Network for Spatial Data
  Abstract The application of deep neural networks in geospatial data has become a trending research problem in the present day. A significant amount of statistical research has already been introduced, such as generalized least square optimization by incorporat…
  crossref Debjoy Thakur 2024-11-05T03:46:50Z 置信度 0.70
• Review for "Artificial neural network encoding of molecular wavefunctions for quantum computing"
  crossref 2024-09-27T00:04:51Z 置信度 0.70
• Review: Provable Observation Noise Robustness for Neural Network Control Systems — R0/PR2
  crossref 2024-02-13T06:55:14Z 置信度 0.70
• House Price Prediction Model Based on Neural Network
  Abstract Through an in-depth understanding of house price prediction issues, the paper aims to establish a BP neural network model for house price prediction based on ideas and methods of the BP neural network. By the BP neural network method, the paper realiz…
  crossref chusheng Wang 2021-09-27T14:38:24Z 置信度 0.70
• Review for "RobMedNAS: searching robust neural network architectures for medical image synthesis"
  crossref 2024-08-14T17:14:57Z 置信度 0.70
• Spiking neural networks for autonomous driving: A review
  crossref Fernando S. Martínez, Jordi Casas-Roma, Laia Subirats, Raúl Parada 2024-10-21T19:28:23Z 置信度 0.70
• Review for "Artificial neural network encoding of molecular wavefunctions for quantum computing"
  crossref 2024-09-27T00:04:51Z 置信度 0.70
• Financial News Summarisation using Transformer Neural Network
  Abstract Transformer architecture, which is based on self-attention mechanism, revolutionised the field of NLP in 2017. It overcame many of the limitations of sequential and iterative approach of the previous popular architectures like LSTM. Generative Pretrai…
  crossref Parth Mihir Patel 2022-10-26T02:07:37Z 置信度 0.70
• Organic neuromorphic spiking circuit for retina-inspired sensory coding and neurotransmitter-mediated neural pathways
  Abstract The fundamental mechanisms of signal communication within the human body rely on the spiking frequency of action potentials. 1,2 Through biological receptors and afferent neuronal cells, stimuli from the external world are encoded into a spiking patte…
  crossref Giovanni Maria Matrone, Eveline van Doremaele, Sophie Griggs, Gang Ye 等 2022-12-08T16:42:35Z 置信度 0.70
• Review for "A Novel Network-Level Fused Self-Attention Deep Neural Network for Cervical Cancer Classification from Cervicography Images"
  crossref 2026-02-28T21:12:57Z 置信度 0.70
• Review for "A Novel Network-Level Fused Self-Attention Deep Neural Network for Cervical Cancer Classification from Cervicography Images"
  crossref 2026-02-28T21:12:57Z 置信度 0.70
• Review: A global monthly climatology of total alkalinity: a neural network approach
  crossref 2018-12-18T16:17:16Z 置信度 0.70
• Review for "Artificial neural network encoding of molecular wavefunctions for quantum computing"
  crossref 2024-09-27T00:04:51Z 置信度 0.70
• Review for "Artificial neural network encoding of molecular wavefunctions for quantum computing"
  crossref 2024-09-27T00:04:51Z 置信度 0.70
• Review for "Artificial neural network encoding of molecular wavefunctions for quantum computing"
  crossref 2024-09-27T00:04:51Z 置信度 0.70
• Review for "Artificial neural network encoding of molecular wavefunctions for quantum computing"
  crossref 2024-09-27T00:04:51Z 置信度 0.70
• Neuromorphic architectures for edge-oriented spiking neural networks: A review
  crossref Kanishka Gunawardana, Sanka Peeris, Kavishka Rambukwella, Roshan Ragel 等 2026-05-30T05:32:38Z 置信度 0.70
• Reconfigurable neural spiking in bias field free spin Hall nano-oscillator
  crossref Sourabh Manna, Rohit Medwal, Rajdeep Singh Rawat 2023-11-14T10:08:38Z 置信度 0.70
• Prediction of Network Security Situation Awareness based on an Improved Model Combined with Neural Network
  Abstract People always pay attention to the security of the network. This paper mainly analyzed the problem of network security situation prediction (NSSP). The Radial Basis Function (RBF) neural network was improved by the particle swarm optimization (PSO) al…
  crossref Li Yuan 2021-04-26T14:29:45Z 置信度 0.70
• Review for "The nonlinear autoregressive network with exogenous inputs (NARX) neural network to damp power system oscillations"
  crossref 2020-07-27T17:06:47Z 置信度 0.70
• Review for "The nonlinear autoregressive network with exogenous inputs (NARX) neural network to damp power system oscillations"
  crossref 2020-07-27T17:06:47Z 置信度 0.70
• Review for "A Novel Network-Level Fused Self-Attention Deep Neural Network for Cervical Cancer Classification from Cervicography Images"
  crossref 2026-02-28T21:12:57Z 置信度 0.70
• Review for "The nonlinear autoregressive network with exogenous inputs (NARX) neural network to damp power system oscillations"
  crossref 2020-07-27T17:06:47Z 置信度 0.70
• Review for "The nonlinear autoregressive network with exogenous inputs (NARX) neural network to damp power system oscillations"
  crossref 2020-07-27T17:06:47Z 置信度 0.70
• Random Networks of Spiking Neurons: Instability in the<b><i>Xenopus</i></b>Tadpole Moto-Neural Pattern
  crossref Carlo Fulvi Mari 2002-07-27T02:19:41Z 置信度 0.70
• Network learning path of university political education based on simulation data and sparse neural network
  Abstract In the face of the impact of the New Coronary Pneumonia epidemic, Schools need to actively engage in online teaching in response to the Ministry of Education's call for "uninterrupted teaching". Ideological and political education is an important way …
  crossref Kaixuan Shao 2023-02-21T17:23:22Z 置信度 0.70
• Pipeline Parallelism with Reduced Network Communications for Efficient Compute-intensive Neural Network Training
  Abstract Pipeline parallelism is a distributed deep neural network training method suitable for tasks that consume large amounts of memory. However, this method entails a large amount of overhead because of the dependency between devices in performing forward …
  crossref Chanhee Yu, Kyongseok Park 2023-11-20T06:40:29Z 置信度 0.70
• Network Traffic Prediction Based on the Multi-time Granularity GRU-BP Neural Network
  Abstract A multi-time granularity GRU-BP neural network is proposed in this study for network traffic prediction. In the method, the network traffic data is fitted firstly by the cubic spline curve, and the fitted data is extracted according to different time …
  crossref wang haipeng, Shuai Zhang 2023-08-18T04:24:14Z 置信度 0.70
• Graph Neural Network: Review of Models, Challenges and Frontier Applications
  crossref Zirui Zhu 2026-07-31T09:12:18Z 置信度 0.70
• A Practical Tutorial on Spiking Neural Networks: Comprehensive Review, Models, Experiments, Software Tools, and Implementation Guidelines
  Spiking neural networks (SNNs) provide a biologically inspired, event-driven alternative to artificial neural networks (ANNs), potentially delivering competitive accuracy at substantially lower energy. This tutorial-study offers a unified, practice-oriented as…
  crossref Bahgat Ayasi, Cristóbal J. Carmona, Mohammed Saleh, Angel M. García-Vico 2025-11-03T14:00:33Z 置信度 0.70
• Advances in Neuromorphic Spin-Based Spiking Neural Networks: A review
  crossref Gaurav Verma, Namita Bindal, Arshid Nisar, Seema Dhull 等 2021-08-13T15:54:40Z 置信度 0.70
• Peer Review Report For: Graph neural network-based anomaly detection for river network systems [version 1; peer review: 2 approved with reservations]
  crossref 2025-11-25T14:52:05Z 置信度 0.70
• CTP-Hybrid: From Hybrid Architecture to Native Spiking Foundation — A Two-Phase Report on Consumer-GPU Spiking LLMs
  Abstract We present the complete two-phase development of CTP-Hybrid, a causal-topological pulsing architecture for large language models. Phase 1 established the first reproducible 7B-scale spiking-augmented LLM fine-tuning on an 8 GB consumer GPU (NVIDIA RTX…
  crossref Shutong Hou 2026-05-15T06:28:07Z 置信度 0.70
• A review of methods for spike sorting: the detection and classification of neural action potentials
  crossref Michael Lewicki 2002-08-24T22:35:54Z 置信度 0.70
• Exceptional Adversarial Robustness Through Architectural Design: A Comparative Study of Classical and Spiking Neural Networks
  Adversarial attacks pose a significant threat to the deployment of deep neural networks in safetycritical applications. Achieving robustness without sacrificing clean accuracy remains a key challenge. In this work, we show that careful architectural design alo…
  crossref Abraham Itzhak Weinberg 2026-03-16T17:30:59Z 置信度 0.70
• Solving graph algorithms with networks of spiking neurons
  crossref D.M. Sala, K.J. Cios 2002-08-24T19:16:32Z 置信度 0.70
• Decision making under uncertainty in a spiking neural network model of the basal ganglia
  crossref Charlotte Héricé, Radwa Khalil, Marie Moftah, Thomas Boraud 等 2016-12-22T01:23:18Z 置信度 0.70
• Area- and Energy-Efficient STDP Learning Algorithm for Spiking Neural Network SoC
  crossref Giseok Kim, Kiryong Kim, Sara Choi, Hyo Jung Jang 等 2020-12-02T21:17:05Z 置信度 0.70
• A cerebellum inspired spiking neural network as a multi-model for pattern classification and robotic trajectory prediction
  Spiking neural networks were introduced to understand spatiotemporal information processing in neurons and have found their application in pattern encoding, data discrimination, and classification. Bioinspired network architectures are considered for event-dri…
  crossref Asha Vijayan, Shyam Diwakar 2022-11-28T05:18:15Z 置信度 0.70
• TM-SNN: Threshold Modulated Spiking Neural Network for Multi-task Learning
  crossref Paolo G. Cachi, Sebastián Ventura Soto, Krzysztof J. Cios 2023-09-30T18:02:23Z 置信度 0.70
• Concepts of Machine Learning
  This chapter introduces the fundamental concepts and principles of machine learning, serving as a theoretical foundation for the subsequent chapters of the book. It provides a comprehensive overview of the main learning paradigms, including supervised, unsuper…
  crossref Yousef Farhang 2026-03-19T11:20:19Z 置信度 0.70
• Decision letter for "Energy-aware spike budgeting for continual learning in spiking neural networks for neuromorphic vision"
  crossref 2026-07-03T23:27:36Z 置信度 0.70
• Routing brain traffic through the von Neumann bottleneck: Efficient cache usage in spiking neural network simulation code on general purpose computers
  crossref J. Pronold, J. Jordan, B.J.N. Wylie, I. Kitayama 等 2022-07-13T11:53:55Z 置信度 0.70
• Hyperparameters optimization of evolving spiking neural network using artificial bee colony for unsupervised anomaly detection
  Abstract Nowadays, anomaly detection in streaming data has gained considerable attention due to the exponential growth in the data gathered by Internet of Things applications. Analyzing and processing vast data volumes requires a system capable of working in r…
  crossref Rabie Rehan, Shahnorbanun Sahran, Zaid Abdi Alkareem Alyasseri, Nor Samsiah Sani 等 2025-07-22T14:56:42Z 置信度 0.70
• A Review of Recent Advances and Application for Spiking Neural Networks
  crossref Hao Liu, Hongfeng Chai, Quan Sun, Xin Yun 等 2024-01-15T09:18:17Z 置信度 0.70
• Event-Based Depth Prediction With Deep Spiking Neural Network
  crossref Xiaoshan Wu, Weihua He, Man Yao, Ziyang Zhang 等 2024-07-10T17:35:03Z 置信度 0.70
• Quantum-inspired complex spiking neural network for multi-source data joint classification
  crossref Yang Liu, Yahui Li, Haige Xu, Yinghao Lin 2025-07-22T16:05:19Z 置信度 0.70
• Finger Vein Recognition Based on Unsupervised Spiking Neural Network
  crossref Li Yang, Xiang Xu, Qiong Yao 2023-12-01T06:03:13Z 置信度 0.70
• An On-chip Spiking Neural Network for Estimation of the Head Pose of the iCub Robot
  crossref Raphaela Kreiser, Alpha Renner, Vanessa R. C. Leite, Baris Serhan 等 2020-06-23T15:01:16Z 置信度 0.70
• Fully-Integrated Spiking Neural Network Using SiO_x-Based RRAM as Synaptic Device
  crossref Amir REGEV, Alessandro BRICALLI, Giuseppe PICCOLBONI, Alexandre VALENTIAN 等 2020-04-24T01:16:57Z 置信度 0.70
• Probabilistic Spiking Neural Network for Robotic Tactile Continual Learning
  crossref Senlin Fang, Yiwen Liu, Chengliang Liu, Jingnan Wang 等 2024-08-08T17:51:05Z 置信度 0.70