Výsledky vyhľadávania - "learning systems"

LMVD: A large-scale multimodal vlog dataset for depression detection in the wild

Autori: He, Lang Chen, Kai Zhao, Junnan a ďalší

Zdroj: Information Fusion. 126(B):1-11

Predmety: Deep Learning, Depression Detection, Multimodal, Transformer, Vlog, Behavioral Research, Data Privacy, Human Computer Interaction, Interactive Computer Systems, Large Datasets, Learning Systems, Multimedia Systems, Academic Achievements, Large-scales, Multi-modal, Multiple Dimensions, Overall Quality, Quality Of Life

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-57350
https://doi.org/10.1016/j.inffus.2025.103632

The practices and politics of machine learning: a field guide for analyzing artificial intelligence

Autori: Lee, Francis, 1974

Zdroj: AI & Society. 40(8):6135-6148

Predmety: Algorithmic assemblages, Critical AI studies, Data practices, Machine learning ethnography, Moments of translation, Science and technology studies, Clustering algorithms, Learning algorithms, Learning systems, Machine learning, Algorithm study, Algorithmic assemblage, Algorithmics, Critical AI study, Machine learning systems, Machine-learning, Moment of translation, Vector spaces

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-57764
https://doi.org/10.1007/s00146-025-02430-7

Sample Selection Methods for Federated Continual Learning in a Time Series Context

Autori: Ickin, Selim Lan, Xiaoyu Angelova, Milena a ďalší

Zdroj: IEEE Access. 13:189057-189073

Predmety: AI-native networks, AI/ML model lifecycle management, catastrophic forgetting, concept drift, Federated continual learning, future mobile networks, sample selection, time series data, Complex networks, Data aggregation, Data reduction, Federated learning, Information management, Learning systems, Life cycle, Mobile telecommunication systems, Reconfigurable hardware, Sampling, Spatio-temporal data, Time series, Time varying networks, AI-native network, AI/machine learning model lifecycle management, Concept drifts, Continual learning, Future mobile network, Lifecycle management, Machine learning models, Samples selection, Time-series data, Behavioral research, Digital storage

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-28916
https://doi.org/10.1109/ACCESS.2025.3628353

Predicting Remaining Useful Life with Sparse Measurement Data

Autori: Karlsson, Jonas Karlsson, Alexander Bekar, Ebru Turanoglu a ďalší

Zdroj: TPdM-Trustworthy Predictive Maintenance IFAC-PapersOnLine. (10):2736-2741

Predmety: ball-bar system, Bayesian deep learning, deep neural network, predictive maintenance, Remaining useful life, Forecasting, Industry 4.0, Learning systems, Machine components, Prediction models, Uncertainty analysis, Ball-bar, Bars system, Bayesian, Learning models, Measurement data, Neural-networks, Remaining useful lives, Deep neural networks, Skövde Artificial Intelligence Lab (SAIL), Virtual Production Development (VPD)

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-25955
https://doi.org/10.1016/j.ifacol.2025.09.460

A Gaussian Process-Regularized Graphical Learning Method for Distribution System State Estimation Using Extremely Scarce State Variable Labels

Autori: Hu, Jiaxiang Xu, Qianwen

Zdroj: IEEE Transactions on Smart Grid. 16(4):3359-3376

Predmety: Estimation, Learning systems, Data models, State estimation, Training, Topology, Biological system modeling, Adaptation models, Uncertainty, Kernel, Distribution system state estimation, semi-supervised learning, Gaussian process, interval state estimation

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-370251
https://doi.org/10.1109/TSG.2025.3552958

P-Blend: Privacy- and Utility-Preserving Blendshape Perturbation Against Re-identification Attacks in Virtual Reality

Autori: Liu, Jingwei Wei, Lai Hu, Yan a ďalší

Zdroj: IEEE Transactions on Visualization and Computer Graphics. 31(11):9592-9602

Predmety: blendshape, Privacy-preservation, virtual reality, Blending, Large datasets, Learning systems, Machine learning, Privacy-preserving techniques, Virtual environments, Blendshapes, Empirical evaluations, Facial animation, Facial Expressions, Privacy preservation, Privacy protection, Random perturbations, Re identifications, Third party application (Apps), User study

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-28780
https://bth.diva-portal.org/smash/get/diva2:2007119/FULLTEXT01.pdf

DropKAN: Dropout Kolmogorov–Arnold Networks

Autori: Altarabichi, Mohammed Ghaith, 1981

Zdroj: IEEE Access. 13:141609-141618

Predmety: Dropout, Dropout Kolmogorov-arnold Networks, Kolmogorov-arnold Networks, Regularization In Neural Networks, Artificial Intelligence, Drops, Learning Systems, Co-adaptation, Dropout Kolmogorov-arnold Network, Kolmogorov, Kolmogorov-arnold Network, Neural-networks, Regularisation, Regularization In Neural Network, Regularization Methods, Chemical Activation

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-57348
https://doi.org/10.1109/ACCESS.2025.3597554

ADF-SL: An Adaptive and Fair Scheme for Smart Learning Task Distribution

Autori: Al-Saedi, Ahmed A. Boeva, Veselka, Professor

Zdroj: IEEE Access. 13:122928-122942

Predmety: Artificial intelligence, efficiency, fairness, layer distribution, split learning, Deep learning, Electrocardiograms, Learning systems, Medical computing, Decentralised, Layer distributions, Learning tasks, Model training, Neural-networks, Performance, Sensitive informations, Task distribution, Health care

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-28486
https://doi.org/10.1109/ACCESS.2025.3586544

Automated assembly quality inspection by deep learning with 2D and 3D synthetic CAD data

Autori: Zhu, Xiaomeng Mårtensson, Pär Hanson, Lars a ďalší

Zdroj: Journal of Intelligent Manufacturing. 36(4):2567-2582

Predmety: Assembly quality inspection, Computer vision, Point cloud, Synthetic data, Transfer learning, Unsupervised domain adaptation, Assembly, Data transfer, Deep learning, Inspection, Learning systems, Assembly quality, Automated assembly, Design data, Domain adaptation, Point-clouds, Quality inspection, Computer aided design, User Centred Product Design, Användarcentrerad produktdesign

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23777
https://doi.org/10.1007/s10845-024-02375-6

A Model of Modern Resilience: Scenes from the Climate Change Frontlines at Tohono O'odham Community College.

Autori: Wilson, Mary Cathleen

Zdroj: Tribal College Journal. Winter2025, Vol. 37 Issue 2, p48-51. 4p. 3 Color Photographs.

Predmety: *NATIVE American universities & colleges, *INTEGRATED learning systems, *CLIMATE change, *CULTURAL maintenance, *INTERDISCIPLINARY education

Fast and Accurate Multi-Neural Network Ensemble Model

Autori: Nakci, Veli Altun, M.

Zdroj: 2025 21st International Conference on Synthesis, Modeling, Analysis and Simulation Methods, and Applications to Circuits Design (SMACD). :1-4

Predmety: Deep Neural Networks, Image Classification, Neural Networks, Transfer Learning Methods, Ensemble Models, High Accuracy, Transfer Learning, Learning Systems, Image Enhancement, Multi-Neural Networks, Ensemble Techniques, Neural Networks Ensemble, Training Time, Ensemble Technique

Prístupová URL adresa: https://hdl.handle.net/20.500.11779/3086
https://doi.org/10.1109/SMACD65553.2025.11091980

Attention-based fuzzy neural networks for self-supervised data annotation

Autori: Islam, Md Rakibul Begum, Shahina Ahmed, Mobyen Uddin, Dr a ďalší

Zdroj: Intelligent Systems with Applications. 28

Predmety: Attention mechanism, Data annotation, Fuzzy neural network, Industry 4.0, Self supervised learning, Data mining, Fuzzy inference, Information fusion, Labeled data, Learning systems, Membership functions, Self-supervised learning, Supervised learning, Attention mechanisms, Domain knowledge, Fuzzy-neural-networks, Heavy duty pumps, Historical data, Pump vibrations, Slurry pumps, Vibration data, Vibration signal, Fuzzy neural networks

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-74558
https://doi.org/10.1016/j.iswa.2025.200610

Predicting corporate innovation using machine learning and social media data

Autori: Ylinen, Mika Ranta, Mikko

Zdroj: Technovation. 148

Predmety: Corporate innovation, Human resource policies, Machine learning, Social media analytics, Textual analysis, Employment, Patents and inventions, Personnel rating, Social networking (online), Technological forecasting, Human resource policy, Innovation performance, Learning media, Machine learning approaches, Machine-learning, Resource policy, Social media, Textual-analysis, Learning systems

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-70026
https://doi.org/10.1016/j.technovation.2025.103322

On-Device Anomaly Detection in Conveyor Belt Operations

Autori: Martinez Rau, Luciano Zhang, Yuxuan Oelmann, Bengt a ďalší

Zdroj: IEEE Open Journal of Instrumentation and Measurement. 4

Predmety: Anomaly Detection, Conveyor Belt, Edge Computing, Industry 4.0, Low-power Microcontroller, Machine Learning, Tinyml, Data Handling, Data Mining, Decision Trees, Failure (mechanical), Heuristic Methods, Learning Systems, Microcontrollers, Pattern Matching, Pattern Recognition Systems, Preventive Maintenance, Random Forests, Bulk Materials, Conveyor Belts, Duty-cycle, F1 Scores, Low-power Microcontrollers, Machine-learning, Mining Operations, Belt Conveyors

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-55661
https://doi.org/10.1109/OJIM.2025.3613073

Improving central apnea detection in preterm infants: Neural network strategies and clinical impact

Autori: Varisco, Gabriele Peng, Z. Niemarkt, H. a ďalší

Zdroj: Computer Methods and Programs in Biomedicine. 272

Predmety: Central Apneas, Machine Learning, Neural Networks, Preterm Infants, Alarm Systems, Biomedical Signal Processing, Convolutional Neural Networks, Electrocardiography, Errors, Image Resolution, Neonatal Monitoring, Statistical Tests, Apnea Detection, Detection Models, Machine-learning, Moving Window, Neonatal Intensive Care Units, Network Strategy, Neural-networks, Time Shifts, Learning Systems

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-73314
https://doi.org/10.1016/j.cmpb.2025.109038

A comprehensive benchmark of machine and deep learning models on structured data for regression and classification

Autori: Shmuel, Assaf Glickman, Oren Lazebnik, Teddy

Zdroj: Neurocomputing. 655

Predmety: Benchmark, Deep learning, Gradient boosting models, Adaptive boosting, Classification (of information), Learning systems, Excel, Gradient boosting, Gradient boosting model, Learning models, Machine-learning, Real-world, Scientific researches, Structured data, article, benchmarking, classification, filtration, machine learning, major clinical study

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-69810
https://doi.org/10.1016/j.neucom.2025.131337

Naming the Pain in machine learning-enabled systems engineering

Autori: Kalinowski, Marcos Mendez, Daniel Giray, Görkem a ďalší

Zdroj: Information and Software Technology. 187

Predmety: Machine learning-enabled system, Survey, Systems engineering, Computer programming, Learning systems, Machine learning, Software engineering, Academic research, Current practices, Current status, Engineering machines, Machine-learning, Operational process, Product process, Qualitative analysis, Status quo, Life cycle

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-28543
https://doi.org/10.1016/j.infsof.2025.107866

It all starts with structure: investigating learning dynamics in large-scale agile software development

Autori: Ahmad, Muhammad Ovais, Associate Professor/Lektor Ghanbari, H. Gustavsson, Tomas a ďalší

Zdroj: Journal of Systems and Software. 230

Predmety: Agile software development, Knowledge sharing, Large-scale agile, Reflexivity, Structural equation modeling, Team cohesion, Team learning, Team structure, Agile manufacturing systems, Computer aided instruction, Knowledge acquisition, Knowledge management, Knowledge transfer, Learning systems, Knowledge-sharing, Large-scales, Learning Activity, Structural equation models, Team structures, Software design, Information Systems, Informatik

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-106428
https://doi.org/10.1016/j.jss.2025.112561

Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach

Autori: Bayram, Firas Ahmed, Bestoun S.

Zdroj: ACM Computing Surveys. 57(5)

Predmety: Contrastive Learning, Dataops, Machine learning operation system, Machine learning systems, Machine-learning, Modeling performance, Modelop, Operation system, Robustness, Trustworthy artificial intelligence, Adversarial machine learning, Computer Science, Datavetenskap

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-103395
https://doi.org/10.1145/3708497

Toward efficient resource utilization at edge nodes in federated learning

Autori: Alawadi, Sadi Ait-Mlouk, Addi Toor, Salman a ďalší

Zdroj: eSSENCE – An eScience Collaboration Progress in Artificial Intelligence. 13(2):101-117

Predmety: Data privacy, Distributed training, Federated learning, Machine learning, Partial training, Training parallelization, Deep learning, Economic and social effects, Learning systems, Edge nodes, Global models, Machine-learning, Model updates, Parallelizations, Resources utilizations

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-26538
https://doi.org/10.1007/s13748-024-00322-3