Výsledky vyhledávání - "ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION"

Unsupervised Motion Retargeting for Human-Robot Imitation

Autoři: Annabi, Louis Ma, Ziqi Nguyen, Sao, Mai a další

Přispěvatelé: Annabi, Louis Ma, Ziqi Nguyen, Sao, Mai a další

Zdroj: HRI 2024 - Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction ; https://hal.science/hal-04401885 ; HRI 2024 - Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, Mar 2024, Boulder (CO), United States. ⟨10.1145/3568294.3580153⟩

Témata: imitation, neural networks, motion retargeting, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geografické téma: Boulder (CO), United States

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2402.05115; ARXIV: 2402.05115

Dostupnost: https://hal.science/hal-04401885
https://hal.science/hal-04401885v1/document
https://hal.science/hal-04401885v1/file/Annabi2024C2AICHI.pdf
https://doi.org/10.1145/3568294.3580153

Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning ; Oups, j'ai échantillonné avec remise : Réinterprétation des intervalles de confiance dans l'apprentissage parcimonieux

Autoři: Lafargue, Raphael Smith, Luke, Anthony Vermet, Franck a další

Přispěvatelé: Lafargue, Raphael Smith, Luke, Anthony Vermet, Franck a další

Zdroj: ISSN: 2835-8856 ; Transactions on Machine Learning Research Journal.

Témata: Few-shot Learning, Statistics, Confidence Intervals, 68T06, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2409.02850; ARXIV: 2409.02850

Dostupnost: https://hal.science/hal-04702128
https://hal.science/hal-04702128v1/document
https://hal.science/hal-04702128v1/file/2678_Oops_I_Sampled_it_Again_R.pdf

VidChapters-7M: Video Chapters at Scale

Autoři: Yang, Antoine Nagrani, Arsha Laptev, Ivan a další

Přispěvatelé: Yang, Antoine Nagrani, Arsha Laptev, Ivan a další

Zdroj: NeurIPS 2023 - Conference on Neural Information Processing Systems - Track on Datasets and Benchmarks ; https://hal.science/hal-04217697 ; NeurIPS 2023 - Conference on Neural Information Processing Systems - Track on Datasets and Benchmarks, Dec 2023, New Orleans (LA), United States

Témata: Data, Video Understanding, Video Chapter Generation, Video Chapter Grounding, Dense Video Captioning, Pretraining, Language Model, Zero-Shot Learning, Computer Vision, Vision and Language, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.7: Natural Language Processing, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.10: Vision and Scene Understanding, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO]Computer Science [cs], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]

Geografické téma: New Orleans (LA), United States

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2309.13952; ARXIV: 2309.13952

Dostupnost: https://hal.science/hal-04217697
https://hal.science/hal-04217697v1/document
https://hal.science/hal-04217697v1/file/view.pdf

Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning

Autoři: Yang, Antoine Nagrani, Arsha Seo, Paul Hongsuck a další

Přispěvatelé: Yang, Antoine Nagrani, Arsha Seo, Paul Hongsuck a další

Zdroj: CVPR 2023 - IEEE/CVF Conference on Computer Vision and Pattern Recognition ; https://inria.hal.science/hal-04039246 ; CVPR 2023 - IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun 2023, Vancouver, Canada

Témata: Computer Vision, Video Understanding, Dense Video Captioning, Video Captioning, Video Paragraph Captioning, Pretraining, Language Model, Few-Shot Learning, Vision and Language, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.7: Natural Language Processing, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.10: Vision and Scene Understanding, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO]Computer Science [cs], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]

Geografické téma: Vancouver

Time: Vancouver, Canada

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2302.14115; ARXIV: 2302.14115

Dostupnost: https://inria.hal.science/hal-04039246
https://inria.hal.science/hal-04039246v1/document
https://inria.hal.science/hal-04039246v1/file/vid2seq.pdf

MultiMediate '23: Engagement Estimation and Bodily Behaviour Recognition in Social Interactions

Autoři: Müller, Philipp Balazia, Michal Baur, Tobias a další

Přispěvatelé: Müller, Philipp Balazia, Michal Baur, Tobias a další

Zdroj: MM 2023 - The 31st ACM International Conference on Multimedia ; https://hal.science/hal-04330332 ; MM 2023 - The 31st ACM International Conference on Multimedia, ACM, Oct 2023, Ottawa, Canada. pp.9640-9645, ⟨10.1145/3581783.3613851⟩

Témata: challenge, dataset, engagement, nonverbal behaviour, Computing methodologies, Artificial intelligence, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geografické téma: Ottawa

Time: Ottawa, Canada

Dostupnost: https://hal.science/hal-04330332
https://hal.science/hal-04330332v1/document
https://hal.science/hal-04330332v1/file/2023_ACMMM.pdf
https://doi.org/10.1145/3581783.3613851

Multimodal Vision Transformers with Forced Attention for Behavior Analysis

Autoři: Agrawal, Tanay Balazia, Michal Müller, Philipp a další

Přispěvatelé: Agrawal, Tanay Balazia, Michal Müller, Philipp a další

Zdroj: WACV '23: IEEE International Winter Conference on Applications in Computer Vision ; https://hal.science/hal-03936484 ; WACV '23: IEEE International Winter Conference on Applications in Computer Vision, IEEE/CVF, Jan 2023, Waikoloa, United States. ⟨10.1109/WACV56688.2023.00339⟩

Témata: miltimodal transformer, personality recognition, behavior detection, 68T05, 68T10, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]

Geografické téma: Waikoloa, United States

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2212.03968; ARXIV: 2212.03968

Dostupnost: https://hal.science/hal-03936484
https://hal.science/hal-03936484v1/document
https://hal.science/hal-03936484v1/file/WACV_2023__Multimodal_Vision_Transformers_with_Forced_Attention_for_Behavior_Analysis.pdf
https://doi.org/10.1109/WACV56688.2023.00339

Few and Fewer: Learning better from few examples using fewer base classes ; Moins et encore moins: Apprendre mieux avec peu d'exemples en utilisant moins de classes génériques.

Autoři: Lafargue, Raphael Bendou, Yassir Pasdeloup, Bastien a další

Přispěvatelé: Lafargue, Raphael Bendou, Yassir Pasdeloup, Bastien a další

Zdroj: https://hal.science/hal-04737094 ; 2024.

Témata: Data-centric, Transfer learning, Few shot learning, 68T, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2401.15834; ARXIV: 2401.15834

Dostupnost: https://hal.science/hal-04737094
https://hal.science/hal-04737094v1/document
https://hal.science/hal-04737094v1/file/2401.15834v1.pdf

Zero-Shot Video Question Answering via Frozen Bidirectional Language Models

Autoři: Yang, Antoine Miech, Antoine Sivic, Josef a další

Přispěvatelé: Yang, Antoine Miech, Antoine Sivic, Josef a další

Zdroj: NeurIPS 2022 - 36th Conference on Neural Information Processing Systems ; https://inria.hal.science/hal-03807016 ; NeurIPS 2022 - 36th Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States

Témata: Video Understanding, Video Question Answering, Zero-Shot Learning, Computer Vision, Vision and Language, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.7: Natural Language Processing, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.10: Vision and Scene Understanding, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, [INFO]Computer Science [cs], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]

Geografické téma: New Orleans, United States

Dostupnost: https://inria.hal.science/hal-03807016
https://inria.hal.science/hal-03807016v2/document
https://inria.hal.science/hal-03807016v2/file/cr.pdf

Bodily Behaviors in Social Interaction: Novel Annotations and State-of-the-Art Evaluation

Autoři: Balazia, Michal Müller, Philipp Tánczos, Ákos Levente a další

Přispěvatelé: Balazia, Michal Müller, Philipp Tánczos, Ákos Levente a další

Zdroj: MM'22: The 30th ACM International Conference on Multimedia ; https://hal.science/hal-03936267 ; MM'22: The 30th ACM International Conference on Multimedia, Oct 2022, Lisbon, Portugal. pp.70-79, ⟨10.1145/3503161.3548363⟩

Témata: Social signals, Behavior detection, Gesture, Body pose, Dataset, 68T05, 68T10, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geografické téma: Lisbon, Portugal

Dostupnost: https://hal.science/hal-03936267
https://hal.science/hal-03936267v2/document
https://hal.science/hal-03936267v2/file/acmmm-main.pdf
https://doi.org/10.1145/3503161.3548363

Multimodal Personality Recognition using Cross-Attention Transformer and Behaviour Encoding

Autoři: Agrawal, Tanay Agarwal, Dhruv Balazia, Michal a další

Přispěvatelé: Agrawal, Tanay Agarwal, Dhruv Balazia, Michal a další

Zdroj: VISAPP '22: International Conference on Computer Vision Theory and Applications ; https://hal.science/hal-03519184 ; VISAPP '22: International Conference on Computer Vision Theory and Applications, IAPR, Feb 2022, virtual, United States. pp.501-508, ⟨10.5220/0010841400003124⟩

Témata: personality recognition, feature engineering, multimodal data, multimodal transformer, 68T05, 68T10, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO]Computer Science [cs], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]

Geografické téma: virtual, United States

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2212.03968; ARXIV: 2212.03968

Dostupnost: https://hal.science/hal-03519184
https://hal.science/hal-03519184v1/document
https://hal.science/hal-03519184v1/file/2021_VISAPP.pdf
https://doi.org/10.5220/0010841400003124

Extracting Microseismic Ground Motion From Legacy Seismograms

Autoři: de Plaen, Raphael S. M. Lecocq, Thomas Lemenkova, Polina a další

Přispěvatelé: de Plaen, Raphael S. M. Lecocq, Thomas Lemenkova, Polina a další

Zdroj: 3rd EUROPEAN CONFERENCE ON EARTHQUAKE ENGINEERING & SEISMOLOGY
Proceedings of the Third European Conference on Earthquake Engineering and Seismology - 3ECEES
https://hal.archives-ouvertes.fr/hal-03774028
Proceedings of the Third European Conference on Earthquake Engineering and Seismology - 3ECEES, European Seismological Commission, Sep 2022, Bucharest, Romania. pp.3507-3513, ⟨10.5281/zenodo.7064711⟩
https://3ecees.ro/

Témata: analog seismograms, seismic noise, oceanic storms, digitalization, machine learning, oceanic climate, ACM: K.: Computing Milieux, ACM: I.: Computing Methodologies, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.10: Image Representation, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.4: Applications, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.5: Reconstruction, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.7: Feature Measurement, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.0: Edge and feature detection, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.1: Pixel classification, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.3: Relaxation, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.2: Region growing, partitioning, [SDU]Sciences of the Universe [physics], [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean

Geografické téma: Bucharest, Romania

Relation: hal-03774028; https://hal.archives-ouvertes.fr/hal-03774028; https://hal.archives-ouvertes.fr/hal-03774028/document; https://hal.archives-ouvertes.fr/hal-03774028/file/De_Plaen_et_al_Proc_3ECEES_2022.pdf

Dostupnost: https://hal.archives-ouvertes.fr/hal-03774028
https://hal.archives-ouvertes.fr/hal-03774028/document
https://hal.archives-ouvertes.fr/hal-03774028/file/De_Plaen_et_al_Proc_3ECEES_2022.pdf
https://doi.org/10.5281/zenodo.7064711

La boîte translucide : un éclairage sur l'intelligence artificielle

Autoři: Jourlin, Pierre Laboratoire Informatique d'Avignon (LIA) Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI

Přispěvatelé: Jourlin, Pierre Laboratoire Informatique d'Avignon (LIA) Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI

Zdroj: https://hal.science/hal-03222107 ; Editions universitaires d'Avignon, 2021, 978-2-35768-127-9 ; https://eua.hypotheses.org/5167.

Témata: ACM: D.: Software, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.7: Natural Language Processing, ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.11: Distributed Artificial Intelligence, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.7: DOCUMENT AND TEXT PROCESSING, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-GL]Computer Science [cs]/General Literature [cs.GL], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET], [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], [INFO.INFO-SD]Computer Science [cs]/Sound [cs.SD], [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing

Dostupnost: https://hal.science/hal-03222107
https://hal.science/hal-03222107v1/document
https://hal.science/hal-03222107v1/file/La%20boite%20translucide%20HAL.pdf

Pooling properties within the Graph Neural network framework ; Propriétés du Pooling dans les réseaux de neurones sur graphes.

Autoři: Brun, Luc Equipe Image - Laboratoire GREYC - UMR6072 Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC) a další

Přispěvatelé: Brun, Luc Equipe Image - Laboratoire GREYC - UMR6072 Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC) a další

Zdroj: https://hal.science/hal-04379337 ; Image - Laboratoire GREYC - UMR6072. 2023.

Témata: Graph Pooling, GNN - Graph Neural Networks, Over-squashing, Over-smoothing, JEL: C - Mathematical and Quantitative Methods, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Dostupnost: https://hal.science/hal-04379337
https://hal.science/hal-04379337v1/document
https://hal.science/hal-04379337v1/file/smoothing_squashing.pdf

R Libraries for Remote Sensing Data Classification by k-means Clustering and NDVI Computation in Congo River Basin, DRC

Autoři: Lemenkova, Polina Debeir, Olivier Ecole Polytechnique de Bruxelles a další

Přispěvatelé: Lemenkova, Polina Debeir, Olivier Ecole Polytechnique de Bruxelles a další

Zdroj: ISSN: 2076-3417.

Témata: Image analyis, image processing, remote sensing, Landsat, R language, programming, cartography, mapping, data visualization, NDVI, Africa, Congo, Rainforest, Land cover change, Computer science, Engineering, Forest, Sub-saharan Africa, Algorithm, Data Analysis, ACM: K.: Computing Milieux, ACM: I.: Computing Methodologies, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.1: Digitization and Image Capture, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS, 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.4.8: Scene Analysis, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.7: Feature Measurement

Relation: hal-03894159; https://hal.science/hal-03894159; https://hal.science/hal-03894159/document; https://hal.science/hal-03894159/file/applsci-12-12554-v2.pdf

Dostupnost: https://hal.science/hal-03894159
https://hal.science/hal-03894159/document
https://hal.science/hal-03894159/file/applsci-12-12554-v2.pdf
https://doi.org/10.3390/app122412554

Satellite Image Processing by Python and R Using Landsat 9 OLI/TIRS and SRTM DEM Data on Côte d'Ivoire, West Africa

Autoři: Lemenkova, Polina Debeir, Olivier Ecole Polytechnique de Bruxelles a další

Přispěvatelé: Lemenkova, Polina Debeir, Olivier Ecole Polytechnique de Bruxelles a další

Zdroj: ISSN: 2313-433X ; Journal of Imaging ; https://hal.archives-ouvertes.fr/hal-03869942 ; Journal of Imaging, 2022, 8 (12), pp.317. ⟨10.3390/jimaging8120317⟩ ; https://www.mdpi.com/2313-433X/8/12/317.

Témata: image analysis, geoinformatics, Computer science, Image processing, remote sensing, programming, Python, satellite image, digital terrain model, cartography, mapping, spatial analysis, Africa, 91.10.Da, 91.10.Jf, 91.10.Sp, 91.10.Xa, 96.25.Vt, 91.10.Fc, 95.40.+s, 95.75.Qr, 95.75.Rs, 42.68.Wt, ACM: I.: Computing Methodologies, ACM: K.: Computing Milieux, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.10: Image Representation, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING

Relation: hal-03869942; https://hal.archives-ouvertes.fr/hal-03869942; https://hal.archives-ouvertes.fr/hal-03869942v2/document; https://hal.archives-ouvertes.fr/hal-03869942v2/file/jimaging-08-00317-v2.pdf

Dostupnost: https://hal.archives-ouvertes.fr/hal-03869942
https://hal.archives-ouvertes.fr/hal-03869942v2/document
https://hal.archives-ouvertes.fr/hal-03869942v2/file/jimaging-08-00317-v2.pdf
https://doi.org/10.3390/jimaging8120317

Computer Vision Algorithms of DigitSeis for Building a Vectorised Dataset of Historical Seismograms from the Archive of Royal Observatory of Belgium

Autoři: Lemenkova, Polina Plaen, Raphaël Lecocq, Thomas a další

Přispěvatelé: Lemenkova, Polina Plaen, Raphaël Lecocq, Thomas a další

Zdroj: ISSN: 1424-8220 ; Sensors ; https://hal.archives-ouvertes.fr/hal-03909569 ; Sensors, 2022, 23 (1), pp.56. ⟨10.3390/s23010056⟩ ; https://www.mdpi.com/1424-8220/23/1/56.

Témata: Computer science, seismology, Galitzine seismometer, horizontal component, analogue seismogram, digitising, earthquake recording, ground motions, historical seismograms, seismic waves, Signal processing, ACM: I.: Computing Methodologies, 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.4.8: Scene Analysis, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING, [INFO]Computer Science [cs], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [SDU]Sciences of the Universe [physics], [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], [SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geology, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [PHYS]Physics [physics], [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]

Relation: hal-03909569; https://hal.archives-ouvertes.fr/hal-03909569; https://hal.archives-ouvertes.fr/hal-03909569/document; https://hal.archives-ouvertes.fr/hal-03909569/file/sensors-23-00056.pdf

Dostupnost: https://hal.archives-ouvertes.fr/hal-03909569
https://hal.archives-ouvertes.fr/hal-03909569/document
https://hal.archives-ouvertes.fr/hal-03909569/file/sensors-23-00056.pdf
https://doi.org/10.3390/s23010056

Mapping Climate Parameters over the Territory of Botswana Using GMT and Gridded Surface Data from TerraClimate

Autoři: Lemenkova, Polina Université libre de Bruxelles (ULB)

Přispěvatelé: Lemenkova, Polina Université libre de Bruxelles (ULB)

Zdroj: ISSN: 2220-9964 ; ISPRS International Journal of Geo-Information ; https://hal.archives-ouvertes.fr/hal-03765979 ; ISPRS International Journal of Geo-Information, MDPI, 2022, 11 (9), pp.473. ⟨10.3390/ijgi11090473⟩ ; https://www.mdpi.com/2220-9964/11/9/473.

Témata: Botswana, cartography, climate, computer science, data science, drought, GMT, mapping, programming, Africa, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.4: Graphics Utilities, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.3: Picture/Image Generation, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.6: Methodology and Techniques, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.10: Image Representation, [SDE]Environmental Sciences, [SDE.MCG]Environmental Sciences/Global Changes, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, [INFO]Computer Science [cs], [INFO.INFO-IA]Computer Science [cs]/Computer Aided Engineering, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation

Relation: hal-03765979; https://hal.archives-ouvertes.fr/hal-03765979; https://hal.archives-ouvertes.fr/hal-03765979/document; https://hal.archives-ouvertes.fr/hal-03765979/file/ijgi-11-00473.pdf

Dostupnost: https://hal.archives-ouvertes.fr/hal-03765979
https://hal.archives-ouvertes.fr/hal-03765979/document
https://hal.archives-ouvertes.fr/hal-03765979/file/ijgi-11-00473.pdf
https://doi.org/10.3390/ijgi11090473

Geophysical Mapping of Ghana Using Advanced Cartographic Tool GMT ; Geofizičko kartiranje Gane pomoću naprednog kartografskog alata GMT

Autoři: Lemenkova, Polina Ecole Polytechnique de Bruxelles Université libre de Bruxelles (ULB)

Přispěvatelé: Lemenkova, Polina Ecole Polytechnique de Bruxelles Université libre de Bruxelles (ULB)

Zdroj: ISSN: 1333-896X ; Kartografija i Geoinformacije ; https://hal.archives-ouvertes.fr/hal-03539625 ; Kartografija i Geoinformacije, Hrvatsko Kartografsko Drustvo, 2022, 20 (36), pp.16-37. ⟨10.32909/kg.20.36.2⟩ ; https://kig.kartografija.hr/index.php/kig/article/view/938.

Témata: Ghana, Africa, geophysics, cartography, GMT, QGIS, ACM: I.: Computing Methodologies, 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.4.8: Scene Analysis, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], [SDU.STU.AG]Sciences of the Universe [physics]/Earth Sciences/Applied geology, [SDU.STU.TE]Sciences of the Universe [physics]/Earth Sciences/Tectonics, [INFO]Computer Science [cs], [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], [SDE]Environmental Sciences, [SDE.IE]Environmental Sciences/Environmental Engineering, [SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology

Relation: hal-03539625; https://hal.archives-ouvertes.fr/hal-03539625; https://hal.archives-ouvertes.fr/hal-03539625/document; https://hal.archives-ouvertes.fr/hal-03539625/file/938-2707-1-SM.pdf

Dostupnost: https://hal.archives-ouvertes.fr/hal-03539625
https://hal.archives-ouvertes.fr/hal-03539625/document
https://hal.archives-ouvertes.fr/hal-03539625/file/938-2707-1-SM.pdf
https://doi.org/10.32909/kg.20.36.2

Evaluating land cover types from Landsat TM using SAGA GIS for vegetation mapping based on ISODATA and K-means clustering

Autoři: Lemenkova, Polina Ecole Polytechnique de Bruxelles Université libre de Bruxelles (ULB)

Přispěvatelé: Lemenkova, Polina Ecole Polytechnique de Bruxelles Université libre de Bruxelles (ULB)

Zdroj: ISSN: 0354-9542 ; Acta Agriculturae Serbica ; https://hal.science/hal-03504862 ; Acta Agriculturae Serbica, 2021, 26 (56), pp.159-165. ⟨10.5937/AASer2152159L⟩ ; http://www.afc.kg.ac.rs/index.php/sr/acta/29-acta/acta/1236-vol-26-no-52-2021.

Témata: SAGA GIS, mapping, vegetation, K-means, ISODATA, clustering, cartography, machine learning, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS, 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.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.0: General, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.10: Image Representation, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis, 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.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.3: Object recognition, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.3: Clustering, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.2: Design Methodology, [INFO]Computer Science [cs], [SDE]Environmental Sciences, [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [SDE.MCG]Environmental Sciences/Global Changes, [SDE.IE]Environmental Sciences/Environmental Engineering, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, [SDV.BID]Life Sciences [q-bio]/Biodiversity

Relation: hal-03504862; https://hal.science/hal-03504862; https://hal.science/hal-03504862/document; https://hal.science/hal-03504862/file/9.%20AAS%20356-21%20Lemenkova.pdf

Dostupnost: https://hal.science/hal-03504862
https://hal.science/hal-03504862/document
https://hal.science/hal-03504862/file/9.%20AAS%20356-21%20Lemenkova.pdf
https://doi.org/10.5937/AASer2152159L

Java and Sumatra Segments of the Sunda Trench: Geomorphology and Geophysical Settings Analysed and Visualized by GMT

Autoři: Lemenkova, Polina Schmidt United Institute of Physics of the Earth Moscow (IPE) Russian Academy of Sciences Moscow (RAS)

Přispěvatelé: Lemenkova, Polina Schmidt United Institute of Physics of the Earth Moscow (IPE) Russian Academy of Sciences Moscow (RAS)

Zdroj: ISSN: 0350-3593 ; Glasnik Srpskog Geografskog Drustva ; https://hal.archives-ouvertes.fr/hal-03093633 ; Glasnik Srpskog Geografskog Drustva, 2021, 100 (2), pp.1-23. ⟨10.2298/GSGD2002001L⟩ ; http://glasniksgd.rs/index.php/home/article/view/723.

Témata: Submarine Geomorphology, GMT, Sunda Trench, Indian Ocean, geology, cartography, mapping, earthquake, tectonics, geomorphology, ACM: H.: Information Systems, ACM: I.: Computing Methodologies, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING/I.6.1: Simulation Theory, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING/I.6.5: Model Development, ACM: I.: Computing Methodologies/I.6: SIMULATION AND MODELING/I.6.8: Types of Simulation, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION/I.5.1: Models, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis, 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.4.1: Digitization and Image Capture, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.6: Methodology and Techniques, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.4: Graphics Utilities, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.2: Graphics Systems, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.6: Methodology and Techniques/I.3.6.2: Graphics data structures and data types, ACM: I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.6: Methodology and Techniques/I.3.6.4: Languages, ACM: I.: Computing Methodologies/I.5: PATTERN RECOGNITION, ACM: I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION, [SDE]Environmental Sciences, [SDE.IE]Environmental Sciences/Environmental Engineering

Relation: hal-03093633; https://hal.archives-ouvertes.fr/hal-03093633; https://hal.archives-ouvertes.fr/hal-03093633/document; https://hal.archives-ouvertes.fr/hal-03093633/file/723-1017-1-PB.pdf

Dostupnost: https://hal.archives-ouvertes.fr/hal-03093633
https://hal.archives-ouvertes.fr/hal-03093633/document
https://hal.archives-ouvertes.fr/hal-03093633/file/723-1017-1-PB.pdf
https://doi.org/10.2298/GSGD2002001L