Suchergebnisse - "adaptation models"

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

Autoren: Hu, Jiaxiang Xu, Qianwen

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

Schlagwörter: 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

Dateibeschreibung: print

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

HeRD: Modeling Heterogeneous Degradations for Federated Super-Resolution in Satellite Imagery

Autoren: Khan, Bostan Mousavi, Seyedhamidreza Daneshtalab, Masoud

Quelle: IEEE Access. 13:125857-125868

Schlagwörter: Degradation, Satellite images, Satellites, Remote sensing, Training, Federated learning, Data models, Anisotropic, Superresolution, Adaptation models, super-resolution, privacy-preserving, heterogeneous data, satellite imagery

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-72921
https://doi.org/10.1109/ACCESS.2025.3590171

Regret Lower Bounds for Learning Linear Quadratic Gaussian Systems

Autoren: Ziemann, Ingvar Sandberg, Henrik

Quelle: IEEE Transactions on Automatic Control. 70(1):159-173

Schlagwörter: Costs, Observability, Adaptation models, Controllability, Adaptive control, Uncertainty, State feedback, closed loop identification, fundamental limits, statistical learning

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-358828
https://kth.diva-portal.org/smash/get/diva2:1929887/FULLTEXT01.pdf

From Missing Pieces to Masterpieces: Image Completion With Context-Adaptive Diffusion

Autoren: Shamsolmoali, Pourya Zareapoor, Masoumeh Zhou, Huiyu et al.

Quelle: IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(7):6073-6087

Schlagwörter: Diffusion models, Solid modeling, Training, Noise reduction, Adaptation models, Image reconstruction, Diffusion processes, Degradation, Coherence, Transformers, Image completion, diffusion models, context-adaptive discrepancy

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-215351
https://arxiv.org/pdf/2504.14294

Fusing Echocardiography Images and Medical Records for Continuous Patient Stratification

Autoren: Painchaud, Nathan Stym-Popper, Jérémie Courand, Pierre-Yves et al.

Weitere Verfasser: Painchaud, Nathan Stym-Popper, Jérémie Courand, Pierre-Yves et al.

Quelle: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 72:1388-1400

Schlagwörter: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Computer Vision and Pattern Recognition (cs.CV), Data models, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Adaptation models, Deep learning, 3. Good health, Machine Learning (cs.LG), Machine Learning, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Artificial Intelligence (cs.AI), Artificial Intelligence, Transformers, Medical services, Hypertension, Pathology, Feature extraction, Training, Computer Vision and Pattern Recognition, Data mining

Zugangs-URL: http://arxiv.org/abs/2401.07796

Towards Explainable AI in Cardiac Diagnostic: Attention-Based Interpretation of Brugada Syndrome

Autoren: Eros Pasero Alessandro Casella Vincenzo Randazzo

Quelle: 2025 IEEE International Conference on Artificial Intelligence for Learning and Optimization (ICoAILO). :1-6

Schlagwörter: Adaptation models, Accuracy, Uncertainty, Neural networks, Decision making, Machine learning, Electrocardiography, Lead, Death, Delays, Neural Networks, Brugada Syndrome, ECG Classification, Artificial Intelligence in Cardiology, Sudden Cardiac Death

Zugangs-URL: https://hdl.handle.net/11583/3003613
https://doi.org/10.1109/ICoAILO66760.2025
https://ieeexplore.ieee.org/document/11155988

Dynamic In-node Group-Aware Scheduling for Multi-Tenant Machine Learning Services on Kubernetes

Autoren: Liu, Peini Guitart Fernández, Jordi

Quelle: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

Schlagwörter: Monitoring, Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors, Resource management, Processor scheduling, Machine learning, Cloud computing, Adaptation models, Dynamic scheduling, Residual neural networks, Throughput, Containers

Dateibeschreibung: application/pdf

Entropy and Memory Aware Active Transfer Learning in Smart Sensing Systems

Autoren: Alam, Umair Farhan, Asma Ahmad Kanwal, Summrina et al.

Quelle: IEEE Access. 12:88841-88861

Schlagwörter: Human activity recognition, Real-time systems, Adaptation models, Entropy, Training, Transfer learning, Support vector machines, Machine learning, Internet of Things, Wearable sensors, Active transfer learning (ATL), Human activity recognition (HAR), Internet of Things (IoT), Machine learning (ML), Ubiquitous computing, Wearable sensor devices

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-350904
https://doi.org/10.1109/ACCESS.2024.3412653

Rao-Blackwellized Particle Filter Using Noise Adaptive Kalman Filter for Fully Mixing State-Space Models

Autoren: Badar, Tabish Särkkä, Simo Zhao, Zheng et al.

Quelle: IEEE Transactions on Aerospace and Electronic Systems. 60(5):6972-6982

Schlagwörter: Noise, Bayes methods, Kalman filters, Adaptation models, Monte Carlo methods, Vectors, State-space methods, Adaptive Kalman filter, Monte Carlo (MC) methods, particle filter, Rao-Blackwellization, Tikhonov regularization, tracking, variational Bayesian (VB) methods

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-543135
https://doi.org/10.1109/TAES.2024.3409644

Adaptive Basis Function Selection for Computationally Efficient Predictions

Autoren: Kullberg, Anton Viset, Frida Skog, Isaac et al.

Quelle: Wallenberg AI, Autonomous Systems and Software Program (WASP) IEEE Signal Processing Letters. 31:2130-2134

Schlagwörter: Computational modeling, Predictive models, Adaptation models, Data models, Accuracy, Training data, Probabilistic logic, Adaptive signal processing, computational complexity, function approximation, Gaussian processes, WASP_publications

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-206535
https://liu.diva-portal.org/smash/get/diva2:1890083/FULLTEXT01.pdf

Minimizing Human Labeling in Training Deep Models for Pedestrian Intention Prediction

Autoren: Muhammad Naveed Riaz Maciej Wielgosz Antonio M. López

Quelle: Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona

Schlagwörter: Predictive models, Synthetic data, Labeling, Data models, Training, Adaptation models, Computational modeling, Skeleton, Pedestrians, Videos

Dateibeschreibung: application/pdf

Zugangs-URL: https://ddd.uab.cat/record/313066

ALANINE: A Novel Decentralized Personalized Federated Learning for Heterogeneous LEO Satellite Constellation

Autoren: Liang Zhao Shenglin Geng Xiongyan Tang et al.

Quelle: IEEE Transactions on Mobile Computing. 24:6945-6960

Schlagwörter: FOS: Computer and information sciences, Computer Science - Distributed, Parallel, and Cluster Computing, Satellites, Training, Low earth orbit satellites, Adaptation models, Data models, Satellite constellations, Accuracy, Satellite images, Computational modeling, Image processing, LEO Satellite , Edge Computing, Super Resolution, Decentralized Federated Learning, Personalized Federated Learning, Model Pruning, Distributed, Parallel, and Cluster Computing (cs.DC)

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2411.07752
https://hdl.handle.net/2158/1415192
https://doi.org/10.1109/TMC.2025.3545429

Design Space Exploration of an In-Sensor Processor for Object Classification in Ultracompact Time-of-Flight Sensors

Autoren: Andrea Fasolino Rosalba Liguori Luigi Di Benedetto et al.

Quelle: IEEE Sensors Journal. 25:25450-25458

Schlagwörter: Sensors, Accuracy, Calculators, Adaptation models, Convolutional neural networks, Training, Intelligent sensors, Power demand, Space exploration, Single-photon avalanche diodes, Convolutional neural network (CNN), hardware (HW) accelerator, object classification, time-of-flight (ToF), tiny machine learning (ML)

Single Intersection MPC Traffic Signal Control in Presence of Automated Vehicles

Autoren: Francesco Liberati Manuel Donsante Andrea Tortorelli

Quelle: IEEE Transactions on Control Systems Technology. 33:1432-1446

Schlagwörter: Vehicle dynamics, Computational modeling, Adaptation models, Trajectory, Predictive control, Optimization, Mathematical models, Automated vehicles, model predictive control (MPC), traffic light (TL) control, traffic signal control

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11573/1720020
https://doi.org/10.1109/tcst.2024.3449188

Learning-Based NMPC Adaptation for Autonomous Driving Using Parallelized Digital Twin

Autoren: Allamaa, Jean Pierre Patrinos, P. Van Der Auweraer, H. et al.

Quelle: IEEE Transactions on Control Systems Technology

Schlagwörter: FOS: Computer and information sciences, Technology, Standards, STADIUS-24-08, Systems and Control (eess.SY), Tuning, Digital twins, Electrical Engineering and Systems Science - Systems and Control, parameter calibration, Computer Science - Robotics, Automation & Control Systems, Engineering, 0102 Applied Mathematics, FOS: Electrical engineering, electronic engineering, information engineering, Training, black-box optimization, Science & Technology, 4007 Control engineering, mechatronics and robotics, Uncertainty, Adaptation models, Engineering, Electrical & Electronic, simulation to reality transfer (Sim2Real), Autonomous driving (AD), 0906 Electrical and Electronic Engineering, Industrial Engineering & Automation, Calibration, Robotics (cs.RO)

Zugangs-URL: http://arxiv.org/abs/2402.16645

GCN-LG-Trust Model for Attack Detection and Cluster Optimization in Underwater Wireless Sensor Networks

Autoren: Bin Jiang Jiacheng Feng Xuerong Cui et al.

Quelle: IEEE Sensors Journal. 25:25503-25514

Schlagwörter: Clustering algorithms, UMBC Security and Optimization for Networked Globe Laboratory (SONG Lab), Sensors, Graph convolutional network, Attenuation, Adaptation models, Computational modeling, Machine learning algorithms, Underwater wireless sensor network, Wireless sensor networks, LightGBM, Malicious attack, Energy consumption, Hidden Markov models, Clustering network, Trust model, Accuracy

Facilitating Online Petition Topic Categorization in South Korea: A BERT-Based Approach

Autoren: Jae Hyun Son Mate Kovacs Shady Salama et al.

Weitere Verfasser: Jae Hyun Son Mate Kovacs Shady Salama et al.

Quelle: 2025 Eleventh International Conference on eDemocracy & eGovernment (ICEDEG). :198-205

Schlagwörter: Data augmentation, Electronic government, civic tech tools, 11476 Digital Society Initiative, Natural language processing, Open data, Data models, government, 340 Law, Adaptation models, Linguistics, 11068 Centre for Democracy Studies Aarau (C2D), topic categorization, co, BERTbased classification, Portals, online petition, creation, natural language processing, Accuracy, AI in governance, Routing

Dateibeschreibung: Facilitating_Online_Petition_Topic_Categorization_in_South_Korea_A_BERT_Based_Approach.pdf - application/pdf

A Three-Class AI Model for Brugada Syndrome Detection to Improve Diagnostic Accuracy in ECG Analysis

Autoren: Randazzo, Vincenzo Casella, Alessandro Caligari, Silvia et al.

Quelle: 2025 IEEE Medical Measurements & Applications (MeMeA). :1-6

Schlagwörter: Adaptation models, Accuracy, Uncertainty, Neural networks, Decision making, Machine learning, Electrocardiography, Lead, Death, Delays, Neural Networks, Brugada Syndrome, ECG Classification, Artificial Intelligence in Cardiology, Sudden Cardiac Death

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11583/3002112
https://ieeexplore.ieee.org/abstract/document/11067974
https://doi.org/10.1109/memea65319.2025.11067974

BiFold: Bimanual Cloth Folding with Language Guidance

Autoren: Barbany Mayor, Oriol Colomé Figueras, Adrià Torras, Carme

Quelle: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)

Schlagwörter: FOS: Computer and information sciences, Translation, Benchmark testing, Standards, Àrees temàtiques de la UPC::Informàtica::Robòtica, Computer Vision and Pattern Recognition (cs.CV), Adaptation models, Shape, Robotics, Topology, Clothing, Computer Vision and Pattern Recognition, Robustness, Robots, Robotics (cs.RO), Visualization

Dateibeschreibung: application/pdf

Zugangs-URL: http://arxiv.org/abs/2501.16458
https://hdl.handle.net/2117/442287
https://doi.org/10.1109/icra55743.2025.11127549

Grasp Transfer based on Self-Aligning Implicit Representations of Local Surfaces

Autoren: Tekden, Ahmet Ercan Deisenroth, Marc Peter Bekiroglu, Yasemin

Quelle: IEEE Robotics and Automation Letters. 8(10):6315-6322

Schlagwörter: Adaptation models, Perception for Grasping and Manipulation, Deep Learning in Grasping and Manipulation, Training, Grasping, Shape, Codes, Surface reconstruction, Object recognition

Dateibeschreibung: electronic

Zugangs-URL: https://research.chalmers.se/publication/537251
https://research.chalmers.se/publication/537251/file/537251_Fulltext.pdf