Suchergebnisse - "ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical"

The Riemannian Means Field Classifier for EEG-Based BCI Data

Autoren: Andreev, Anton Cattan, Grégoire Congedo, Marco et al.

Weitere Verfasser: Andreev, Anton Cattan, Grégoire Congedo, Marco et al.

Quelle: ISSN: 1424-8220 ; Sensors ; https://hal.science/hal-05043032 ; Sensors, 2025, 25 (7), pp.2305. ⟨10.3390/s25072305⟩.

Schlagwörter: Brain computer interface BCI, P300 classification, Motor Imagery MI, Electroencephalography EEG, Riemannian geometry, Event related potentials ERP, Machine learning ML, Differential geometry, Signal and Image Processing, Interface cerveau machine ICM, Interface cerveau-ordinateur ICO, P300, Potentiel Evoqué Cognitif PEC, Imagination motrice IM, Geometrie riemannienne, Electroencephalograhie EEG, Apprentissage automatique ML, Geometrie differentielle, Traitement du signal et de l'image, Classification du signal EEG, ACM: G.: Mathematics of Computing/G.1: NUMERICAL ANALYSIS/G.1.6: Optimization, ACM: H.: Information Systems/H.5: INFORMATION INTERFACES AND PRESENTATION (e.g., HCI), ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications/I.5.4.1: Signal processing, [SCCO.NEUR]Cognitive science/Neuroscience, [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SCCO]Cognitive science, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2504.17352; ARXIV: 2504.17352

Verfügbarkeit: https://hal.science/hal-05043032
https://hal.science/hal-05043032v1/document
https://hal.science/hal-05043032v1/file/manuscript.v8_HAL.pdf
https://doi.org/10.3390/s25072305

Adaptive Scattering Transforms for Playing Technique Recognition

Autoren: Wang, Changhong Benetos, Emmanouil Lostanlen, Vincent et al.

Weitere Verfasser: Wang, Changhong Benetos, Emmanouil Lostanlen, Vincent et al.

Quelle: IEEE/ACM Transactions on Audio, Speech, and Language Processing

Schlagwörter: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], music performance analysis, 02 engineering and technology, [STAT.CO] Statistics [stat]/Computation [stat.CO], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], Scattering, Wavelet transforms, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], [SHS.STAT] Humanities and Social Sciences/Methods and statistics, Music performance analysis, 0202 electrical engineering, electronic engineering, information engineering, scattering transform, [STAT.CO]Statistics [stat]/Computation [stat.CO], Multiple signal classification, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SHS.MUSIQ]Humanities and Social Sciences/Musicology and performing arts, [SHS.STAT]Humanities and Social Sciences/Methods and statistics, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML], ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, Time-frequency analysis, music signal analysis, [SHS.MUSIQ] Humanities and Social Sciences/Musicology and performing arts, Music signal analysis, Speech processing, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, Explainable artificial intelligence, flute music, Instruments, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Music

Dateibeschreibung: application/pdf

Zugangs-URL: https://hal.science/hal-03629482v2
https://doi.org/10.1109/taslp.2022.3156785
https://hal.science/hal-03629482v2/document

Hierarchical Cluster Analysis by R language for Pattern Recognition in the Bathymetric Data Frame: a Case Study of the Mariana Trench, Pacific Ocean

Autoren: Lemenkova, Polina Ocean University of China (OUC) China Scholarship Council (CSC), Marine Scholarship of China, State Oceanic Administration. Grant reference: 2016SOA002. et al.

Weitere Verfasser: Lemenkova, Polina Ocean University of China (OUC) China Scholarship Council (CSC), Marine Scholarship of China, State Oceanic Administration. Grant reference: 2016SOA002. et al.

Quelle: Virtual Simulation, Prototyping and Industrial Design ; https://hal.archives-ouvertes.fr/hal-01974752 ; Virtual Simulation, Prototyping and Industrial Design, Tambov State Technical University (TSTU), Nov 2018, Tambov, Russia. pp.147-152, ⟨10.6084/m9.figshare.7531550⟩ ; http://go.tstu.ru/meroprijatija.php?id=46&lang=ru

Schlagwörter: R Language, Programming, Algorithm, Oceanographic processes, Cluster Analysis, Pacific Ocean, Hierarchical clustering algorithm, Dendrogram structure, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.0: Algorithms, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering/I.5.3.1: Similarity measures, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications/I.5.4.0: Computer vision, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.3: Picture/Image Generation, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.3: Picture/Image Generation/I.3.3.3: Display algorithms, [INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [SDU.STU.TE]Sciences of the Universe [physics]/Earth Sciences/Tectonics, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geology, [SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology

Geographisches Schlagwort: Tambov, Russia

Relation: hal-01974752; https://hal.archives-ouvertes.fr/hal-01974752; https://hal.archives-ouvertes.fr/hal-01974752/document; https://hal.archives-ouvertes.fr/hal-01974752/file/Conf-Tambov2018-Lemenkova-147-152.pdf

Verfügbarkeit: https://hal.archives-ouvertes.fr/hal-01974752
https://hal.archives-ouvertes.fr/hal-01974752/document
https://hal.archives-ouvertes.fr/hal-01974752/file/Conf-Tambov2018-Lemenkova-147-152.pdf
https://doi.org/10.6084/m9.figshare.7531550

Combining Structure and Parameter Adaptation of HMMs for Printed Text Recognition

Autoren: Ait-Mohand, Kamel Paquet, Thierry Ragot, Nicolas et al.

Weitere Verfasser: Ait-Mohand, Kamel Paquet, Thierry Ragot, Nicolas et al.

Quelle: IEEE Transactions on Pattern Analysis and Machine Intelligence. 36:1716-1732

Schlagwörter: Optimization, Optical character recognition software, parameter adaptation, Character recognition, structure adaptation, historical documents, Data models, Adaptation models, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 02 engineering and technology, 16. Peace & justice, ACM: I.: Computing Methodologies/I.7: DOCUMENT AND TEXT PROCESSING/I.7.5: Document Capture/I.7.5.2: Optical character recognition (OCR), ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing, 03 medical and health sciences, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology/I.5.2.0: Classifier design and evaluation, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], printed text recognition, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, 0202 electrical engineering, electronic engineering, information engineering, Training, Hidden Markov models, 0305 other medical science

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/26352227

Using GIS for Monitoring Lacustrine Ecosystem: a Case Study of Laguna de Gallocanta, Spain

Autoren: Lemenkova, Polina Ocean University of China (OUC) Swiss Government Excellence Scholarships for Foreign Scholars & Artists (ESKAS). Grant reference: 2008-0066/Russland/OP Referenz 675/Bri et al.

Weitere Verfasser: Lemenkova, Polina Ocean University of China (OUC) Swiss Government Excellence Scholarships for Foreign Scholars & Artists (ESKAS). Grant reference: 2008-0066/Russland/OP Referenz 675/Bri et al.

Quelle: Problems of the Environmental Landscape Planning ; https://hal.archives-ouvertes.fr/hal-01974747 ; Problems of the Environmental Landscape Planning, Novocherkasskij inzhenerno-meliorativnyj institut DGAU, Apr 2016, Novocherkassk, Russia. ⟨10.6084/m9.figshare.7210229⟩

Schlagwörter: Satellite image analysis, Image interpretation, Image classification, DEM analysis, DEM modelisation, DEM segmentation, Digital terrain analysis, Digital terrain model, Digital elevation model, Digital elevation model DEM, Spain, Environmental modeling, Hydrological modeling, SIG Systèmes d'information géographique, SIG et modélisation spatiale, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications/I.5.4.0: Computer vision, ACM: K.: Computing Milieux/K.3: COMPUTERS AND EDUCATION, ACM: K.: Computing Milieux/K.3: COMPUTERS AND EDUCATION/K.3.1: Computer Uses in Education, ACM: K.: Computing Milieux/K.3: COMPUTERS AND EDUCATION/K.3.2: Computer and Information Science Education, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.0: Image displays, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]

Geographisches Schlagwort: Novocherkassk, Russia

Relation: hal-01974747; https://hal.archives-ouvertes.fr/hal-01974747; https://hal.archives-ouvertes.fr/hal-01974747/document; https://hal.archives-ouvertes.fr/hal-01974747/file/Lemenkova_Novocherkassk2016.pdf

Verfügbarkeit: https://hal.archives-ouvertes.fr/hal-01974747
https://hal.archives-ouvertes.fr/hal-01974747/document
https://hal.archives-ouvertes.fr/hal-01974747/file/Lemenkova_Novocherkassk2016.pdf
https://doi.org/10.6084/m9.figshare.7210229

Regularized estimation of bathymetry and water quality using hyperspectral remote sensing

Autoren: Jay, Sylvain Guillaume, Mireille, Olwen HIPE (HIPE) et al.

Weitere Verfasser: Jay, Sylvain Guillaume, Mireille, Olwen HIPE (HIPE) et al.

Quelle: ISSN: 0143-1161.

Schlagwörter: remote sensing, estimation, hyperspectral, bathymetry, PACS 02, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.0: Color, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere

Relation: IRSTEA: PUB00045786

Verfügbarkeit: https://hal.science/hal-01279585
https://hal.science/hal-01279585v1/document
https://hal.science/hal-01279585v1/file/pub00045786.pdf
https://doi.org/10.1080/01431161.2015.1125551

Fast and Accurate Texture Recognition with Multilayer Convolution and Multifractal Analysis

Autoren: Badri, Hicham Yahia, Hussein Daoudi, Khalid et al.

Weitere Verfasser: Badri, Hicham Yahia, Hussein Daoudi, Khalid et al.

Quelle: European Conference on Computer Vision ; https://inria.hal.science/hal-01064793 ; European Conference on Computer Vision, ECCV 2014, Sep 2014, Zürich, Switzerland

Schlagwörter: ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.7: Feature Measurement, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD]

Geographisches Schlagwort: Zürich, Switzerland

Verfügbarkeit: https://inria.hal.science/hal-01064793
https://inria.hal.science/hal-01064793/document
https://inria.hal.science/hal-01064793/file/eccv2014.pdf

Learning from Multiple Graphs using a Sigmoid Kernel

Autoren: Ricatte, Thomas Garriga, Gemma, C. Gilleron, Rémi et al.

Weitere Verfasser: Ricatte, Thomas Garriga, Gemma, C. Gilleron, Rémi et al.

Quelle: The 12th International Conference on Machine Learning and Applications (ICMLA'13) ; https://inria.hal.science/hal-00913237 ; The 12th International Conference on Machine Learning and Applications (ICMLA'13), Dec 2013, Miami, United States

Schlagwörter: ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning/I.2.6.6: Parameter learning, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geographisches Schlagwort: Miami, United States

Verfügbarkeit: https://inria.hal.science/hal-00913237
https://inria.hal.science/hal-00913237v1/document
https://inria.hal.science/hal-00913237v1/file/main.pdf

Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clustering

Autoren: Varoquaux, Gaël Gramfort, Alexandre Thirion, Bertrand et al.

Weitere Verfasser: Varoquaux, Gaël Gramfort, Alexandre Thirion, Bertrand et al.

Quelle: International Conference on Machine Learning ; https://inria.hal.science/hal-00705192 ; International Conference on Machine Learning, Andrew McCallum, Jun 2012, Edimbourg, United Kingdom

Schlagwörter: brain imaging, fMRI, Sparse recovery, correlated design, clustering, randomization, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.5: Multivariate statistics, ACM: J.: Computer Applications/J.3: LIFE AND MEDICAL SCIENCES/J.3.0: Biology and genetics, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [STAT.TH]Statistics [stat]/Statistics Theory [stat.TH]

Geographisches Schlagwort: Edimbourg, United Kingdom

Verfügbarkeit: https://inria.hal.science/hal-00705192
https://inria.hal.science/hal-00705192v1/document
https://inria.hal.science/hal-00705192v1/file/paper.pdf

Learning Shape Metrics based on Deformations and Transport

Autoren: Charpiat, Guillaume Perception Understanding Learning Systems for Activity Recognition (PULSAR) Centre Inria d'Université Côte d'Azur et al.

Weitere Verfasser: Charpiat, Guillaume Perception Understanding Learning Systems for Activity Recognition (PULSAR) Centre Inria d'Université Côte d'Azur et al.

Quelle: Second Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment ; https://inria.hal.science/inria-00481535 ; Second Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment, Sep 2009, Kyoto, Japan

Schlagwörter: manifold learning, shape, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.8: Shape, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.2: Geometric, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]

Geographisches Schlagwort: Kyoto, Japan

Time: Kyoto, Japan

Verfügbarkeit: https://inria.hal.science/inria-00481535
https://inria.hal.science/inria-00481535v1/document
https://inria.hal.science/inria-00481535v1/file/learning_shapes_final.pdf

Subset seed automaton

Autoren: Kucherov, Gregory Noé, Laurent Roytberg, Mihkail et al.

Weitere Verfasser: Kucherov, Gregory Noé, Laurent Roytberg, Mihkail et al.

Quelle: CIAA 2007 ; https://hal.inria.fr/inria-00170414 ; CIAA 2007, Jul 2007, Prague, Czech Republic. pp.180-191, ⟨10.1007/978-3-540-76336-9_18⟩ ; http://www.springerlink.com/content/y824l20554002756/

Schlagwörter: ACM: J.: Computer Applications/J.3: LIFE AND MEDICAL SCIENCES/J.3.0: Biology and genetics, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.7: DOCUMENT AND TEXT PROCESSING/I.7.3: Index Generation, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.11: Renewal theory, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]

Geographisches Schlagwort: Prague, Czech Republic

Relation: inria-00170414; https://hal.inria.fr/inria-00170414; https://hal.inria.fr/inria-00170414/document; https://hal.inria.fr/inria-00170414/file/main.pdf

Verfügbarkeit: https://hal.inria.fr/inria-00170414
https://hal.inria.fr/inria-00170414/document
https://hal.inria.fr/inria-00170414/file/main.pdf
https://doi.org/10.1007/978-3-540-76336-9_18

Supervised machine learning with kernel embeddings of fuzzy sets and probability measures

Autoren: Guevara, Jorge Computer vision research group (VISION) institute of mathematics and statistics university of são paulo et al.

Weitere Verfasser: Guevara, Jorge Computer vision research group (VISION) institute of mathematics and statistics university of são paulo et al.

Quelle: https://hal.archives-ouvertes.fr/hal-01317746 ; [Research Report] IME USP. 2016.

Schlagwörter: granular computing, fuzzy sets, kernel method, group anomaly detection, kernel embedding, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.1: Fuzzy set, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology/I.5.2.0: Classifier design and evaluation, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology/I.5.2.2: Pattern analysis, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]

Relation: hal-01317746; https://hal.archives-ouvertes.fr/hal-01317746; https://hal.archives-ouvertes.fr/hal-01317746/document; https://hal.archives-ouvertes.fr/hal-01317746/file/bare_jrnl.pdf

Verfügbarkeit: https://hal.archives-ouvertes.fr/hal-01317746
https://hal.archives-ouvertes.fr/hal-01317746/document
https://hal.archives-ouvertes.fr/hal-01317746/file/bare_jrnl.pdf

A framework for inter-subject prediction of functional connectivity from structural networks

Autoren: Deligianni, Fani Varoquaux, Gaël Thirion, Bertrand et al.

Weitere Verfasser: Deligianni, Fani Varoquaux, Gaël Thirion, Bertrand et al.

Quelle: ISSN: 0278-0062 ; IEEE Transactions on Medical Imaging ; https://inria.hal.science/hal-00852072 ; IEEE Transactions on Medical Imaging, 2013, epub ahead of print, ⟨10.1109/TMI.2013.2276916⟩ ; http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6575192&tag=1.

Schlagwörter: structural brain connectivity, functional brain connectivity, statistical associations, predictive modeling, ACM: J.: Computer Applications/J.3: LIFE AND MEDICAL SCIENCES, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [SCCO.NEUR]Cognitive science/Neuroscience, [SDV.IB]Life Sciences [q-bio]/Bioengineering

Verfügbarkeit: https://inria.hal.science/hal-00852072
https://inria.hal.science/hal-00852072v1/document
https://inria.hal.science/hal-00852072v1/file/paper.pdf
https://doi.org/10.1109/TMI.2013.2276916

A Concentration-Based Adaptive Approach to Region Merging of Optimal Time and Space Complexities

Autoren: Fiorio, Christophe Mas, Andre Image & Interaction (ICAR) et al.

Weitere Verfasser: Fiorio, Christophe Mas, Andre Image & Interaction (ICAR) et al.

Quelle: Proceedings of the British Machine Vision Conference ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-01168062 ; Proceedings of the British Machine Vision Conference, Sep 2000, Bristol, United Kingdom. ⟨10.5244/C.14.78⟩

Schlagwörter: Statistical image analysis, Image analysis, Image processing algorithm, Region segmentation, Region segmentation criterion, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.2: Region growing, partitioning, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]

Geographisches Schlagwort: Bristol, United Kingdom

Time: Bristol, United Kingdom

Verfügbarkeit: https://hal-lirmm.ccsd.cnrs.fr/lirmm-01168062
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01168062v1/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-01168062v1/file/FioNocBMVC00_A%20Concentration-Based%20Adaptive%20Approach%20to%20Region%20Merging%20of%20Optimal%20Time%20and%20Space%20Complexities.pdf
https://doi.org/10.5244/C.14.78

Total variation regularization for fMRI-based prediction of behaviour.

Autoren: Michel, Vincent Gramfort, Alexandre Varoquaux, Gaël et al.

Weitere Verfasser: Michel, Vincent Gramfort, Alexandre Varoquaux, Gaël et al.

Quelle: ISSN: 0278-0062 ; IEEE Transactions on Medical Imaging ; https://inria.hal.science/inria-00563468 ; IEEE Transactions on Medical Imaging, 2011, 30 (7), pp.1328 - 1340. ⟨10.1109/TMI.2011.2113378⟩.

Schlagwörter: ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.9: Applications, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: J.: Computer Applications/J.3: LIFE AND MEDICAL SCIENCES/J.3.1: Health, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/1102.1101; info:eu-repo/semantics/altIdentifier/pmid/21317080; ARXIV: 1102.1101; PUBMED: 21317080

Verfügbarkeit: https://inria.hal.science/inria-00563468
https://inria.hal.science/inria-00563468v1/document
https://inria.hal.science/inria-00563468v1/file/arxiv_version.pdf
https://doi.org/10.1109/TMI.2011.2113378

Microcanonical multifractal formalism--a geometrical approach to multifractal systems: Part I. Singularity analysis

Autoren: Turiel, Antonio Yahia, Hussein Perez-Vicente, Conrad et al.

Weitere Verfasser: Turiel, Antonio Yahia, Hussein Perez-Vicente, Conrad et al.

Quelle: ISSN: 1751-8113 ; EISSN: 1751-8121 ; Journal of Physics A: Mathematical and Theoretical.

Schlagwörter: ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.10: Image Representation, [PHYS.COND.CM-DS-NN]Physics [physics]/Condensed Matter [cond-mat]/Disordered Systems and Neural Networks [cond-mat.dis-nn], [NLIN.NLIN-CD]Nonlinear Sciences [physics]/Chaotic Dynamics [nlin.CD], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing

Relation: hal-00937370; https://hal.inria.fr/hal-00937370; https://hal.inria.fr/hal-00937370/document; https://hal.inria.fr/hal-00937370/file/Turiel-part1-2008.pdf

Verfügbarkeit: https://hal.inria.fr/hal-00937370
https://hal.inria.fr/hal-00937370/document
https://hal.inria.fr/hal-00937370/file/Turiel-part1-2008.pdf
https://doi.org/10.1088/1751-8113/41/1/015501

Network Flow Algorithms for Structured Sparsity

Autoren: Mairal, Julien Jenatton, Rodolphe Obozinski, Guillaume et al.

Weitere Verfasser: Mairal, Julien Jenatton, Rodolphe Obozinski, Guillaume et al.

Quelle: https://inria.hal.science/inria-00512556 ; [Research Report] RR-7372, INRIA. 2010, pp.23.

Schlagwörter: convex optimization, sparsity, sparse methods, proximal methods, network flow optimization, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: G.: Mathematics of Computing/G.3: PROBABILITY AND STATISTICS/G.3.13: Statistical computing, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [STAT.OT]Statistics [stat]/Other Statistics [stat.ML], [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/1008.5209; ARXIV: 1008.5209

Verfügbarkeit: https://inria.hal.science/inria-00512556
https://inria.hal.science/inria-00512556/document
https://inria.hal.science/inria-00512556/file/RR-7372.pdf

Spatiotemporal Atlas Estimation for Developmental Delay Detection in Longitudinal Datasets

Autoren: Durrleman, Stanley Pennec, Xavier Gerig, Guido et al.

Weitere Verfasser: Durrleman, Stanley Pennec, Xavier Gerig, Guido et al.

Quelle: https://inria.hal.science/inria-00408293 ; [Research Report] RR-6952, INRIA. 2009, 17 p.

Schlagwörter: longitudinal data, spatiotemporal variability, 4D registration, time regression, atlas construction, large deformation, diffeomorphism, currents, Computational Anatomy, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology/I.5.2.2: Pattern analysis, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.7: Feature Measurement/I.4.7.4: Size and shape, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.11: Time-varying imagery, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing

Verfügbarkeit: https://inria.hal.science/inria-00408293
https://inria.hal.science/inria-00408293v1/document
https://inria.hal.science/inria-00408293v1/file/RR-6952.pdf

Landscape features that prevent or foster urban sprawl

Autoren: Guyet, Thomas AGROCAMPUS OUEST Diagnosing, Recommending Actions and Modelling (DREAM) et al.

Weitere Verfasser: Guyet, Thomas AGROCAMPUS OUEST Diagnosing, Recommending Actions and Modelling (DREAM) et al.

Quelle: MultiTemp 2015 : 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images ; https://inria.hal.science/hal-01178944 ; MultiTemp 2015 : 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images, Jul 2015, Annecy, France. pp.244-247 ; http://www.multitemp2015.org/

Schlagwörter: principal component analysis, statistical analysis, Remote sensing, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General/I.4.0.1: Image processing software, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.10: Image Representation/I.4.10.3: Statistical, [INFO]Computer Science [cs]

Geographisches Schlagwort: Annecy, France

Verfügbarkeit: https://inria.hal.science/hal-01178944

Probabilistic Relational Models with Clustering Uncertainty

Autoren: Coutant, Anthony Philippe, Leray Le Capitaine, Hoel et al.

Weitere Verfasser: Coutant, Anthony Philippe, Leray Le Capitaine, Hoel et al.

Quelle: IEEE International Joint Conference on Neural Networks (IJCNN 2015) ; https://hal.science/hal-01183563 ; IEEE International Joint Conference on Neural Networks (IJCNN 2015), Jul 2015, Killarney, Ireland

Schlagwörter: Probabilistic Relational Models, Structure Learning, Clustering, Reference Uncertainty, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models/I.5.1.4: Statistical, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]

Geographisches Schlagwort: Killarney, Ireland

Verfügbarkeit: https://hal.science/hal-01183563