Artigos de revistas sobre o tema "Imagerie Subsalt"
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Wang, Lin, Hisao-Chi Li, Bai Xue e Chein-I. Chang. "Constrained Band Subset Selection for Hyperspectral Imagery". IEEE Geoscience and Remote Sensing Letters 14, n.º 11 (novembro de 2017): 2032–36. http://dx.doi.org/10.1109/lgrs.2017.2749209.
Texto completo da fonteWang, Lin, Chein-I. Chang, Li-Chien Lee, Yulei Wang, Bai Xue, Meiping Song, Chuanyan Yu e Sen Li. "Band Subset Selection for Anomaly Detection in Hyperspectral Imagery". IEEE Transactions on Geoscience and Remote Sensing 55, n.º 9 (setembro de 2017): 4887–98. http://dx.doi.org/10.1109/tgrs.2017.2681278.
Texto completo da fonteZhao, Yong-Qiang, Lei Zhang e Seong G. Kong. "Band-Subset-Based Clustering and Fusion for Hyperspectral Imagery Classification". IEEE Transactions on Geoscience and Remote Sensing 49, n.º 2 (fevereiro de 2011): 747–56. http://dx.doi.org/10.1109/tgrs.2010.2059707.
Texto completo da fonteMorenikeji, G. B., O. O. Idowu, B. M. Adeleye, O. R. Bankole e T. W. Anjide. "Effects of Population Increase on Peri-Urban Land Growth in Asa Local Government Area, Kwara State". Environmental Technology and Science Journal 14, n.º 1 (1 de agosto de 2023): 180–88. http://dx.doi.org/10.4314/etsj.v14i1.19.
Texto completo da fonteYe, Bei, Shufang Tian, Qiuming Cheng e Yunzhao Ge. "Application of Lithological Mapping Based on Advanced Hyperspectral Imager (AHSI) Imagery Onboard Gaofen-5 (GF-5) Satellite". Remote Sensing 12, n.º 23 (6 de dezembro de 2020): 3990. http://dx.doi.org/10.3390/rs12233990.
Texto completo da fonteWilliams, Sarah E., e Jennifer Cumming. "Measuring Athlete Imagery Ability: The Sport Imagery Ability Questionnaire". Journal of Sport and Exercise Psychology 33, n.º 3 (junho de 2011): 416–40. http://dx.doi.org/10.1123/jsep.33.3.416.
Texto completo da fonteLiu, Yufei, Xiaorun Li, Ziqiang Hua e Liaoying Zhao. "EBARec-BS: Effective Band Attention Reconstruction Network for Hyperspectral Imagery Band Selection". Remote Sensing 13, n.º 18 (9 de setembro de 2021): 3602. http://dx.doi.org/10.3390/rs13183602.
Texto completo da fonteDi, Wei, Quan Pan, Yong-qiang Zhao e Lin He. "Anomaly Target Detection in Hyperspectral Imagery Based on Band Subset Fusion by Fuzzy Integral". Journal of Electronics & Information Technology 30, n.º 2 (24 de fevereiro de 2011): 267–71. http://dx.doi.org/10.3724/sp.j.1146.2006.01140.
Texto completo da fonteCorlett, John T., John Anton, Steve Kozub e Michel Tardif. "Is Locomotor Distance Estimation Guided by Visual Imagery?" Perceptual and Motor Skills 69, n.º 3_suppl (dezembro de 1989): 1267–72. http://dx.doi.org/10.2466/pms.1989.69.3f.1267.
Texto completo da fonteCorlett, John T., John Anton, Steve Kozub e Michel Tardif. "Is Locomotor Distance Estimation Guided by Visual Imagery?" Perceptual and Motor Skills 69, n.º 3-2 (dezembro de 1989): 1267–72. http://dx.doi.org/10.1177/00315125890693-237.
Texto completo da fonteAdam, Fathalrahman, Thomas Esch e Mihai Datcu. "Feature Investigation for Large Scale Urban Detection Using Landsat Imagery". Proceedings 2, n.º 7 (22 de março de 2018): 349. http://dx.doi.org/10.3390/ecrs-2-05162.
Texto completo da fonteBaig, Muhammad Zeeshan, Nauman Aslam, Hubert P. H. Shum e Li Zhang. "Differential evolution algorithm as a tool for optimal feature subset selection in motor imagery EEG". Expert Systems with Applications 90 (dezembro de 2017): 184–95. http://dx.doi.org/10.1016/j.eswa.2017.07.033.
Texto completo da fonteWang, Jie, Zuren Feng, Xiaodong Ren, Na Lu, Jing Luo e Lei Sun. "Feature subset and time segment selection for the classification of EEG data based motor imagery". Biomedical Signal Processing and Control 61 (agosto de 2020): 102026. http://dx.doi.org/10.1016/j.bspc.2020.102026.
Texto completo da fonteAmorim, André, Bruno Travassos e Pedro Mendes. "Imagery ability in Boccia: Comparison among federate athletes from different medical sport groups". Motricidade 13, n.º 4 (27 de janeiro de 2018): 46. http://dx.doi.org/10.6063/motricidade.11780.
Texto completo da fonteHewahi, Nabil M., e Eyad A. Alashqar. "Wrapper Feature Selection based on Genetic Algorithm for Recognizing Objects from Satellite Imagery". Journal of Information Technology Research 8, n.º 3 (julho de 2015): 1–20. http://dx.doi.org/10.4018/jitr.2015070101.
Texto completo da fonteAnand, Raju, Sathishkumar Samiaappan, Shanmugham Veni, Ethan Worch e Meilun Zhou. "Airborne Hyperspectral Imagery for Band Selection Using Moth–Flame Metaheuristic Optimization". Journal of Imaging 8, n.º 5 (27 de abril de 2022): 126. http://dx.doi.org/10.3390/jimaging8050126.
Texto completo da fonteSamadzadegan, Farhad, e Hadiseh Hasani. "Determination Optimum SVMs Classifiers for Hyperspectral Imagery Based on Ant Colony Optimization". Key Engineering Materials 500 (janeiro de 2012): 792–98. http://dx.doi.org/10.4028/www.scientific.net/kem.500.792.
Texto completo da fonteSuárez Rozo, Manuel Enrique, Sara Trapero-Asenjo, Daniel Pecos-Martín, Samuel Fernández-Carnero, Tomás Gallego-Izquierdo, José Jesús Jiménez Rejano e Susana Nunez-Nagy. "Reliability of the Spanish Version of the Movement Imagery Questionnaire-3 (MIQ-3) and Characteristics of Motor Imagery in Institutionalized Elderly People". Journal of Clinical Medicine 11, n.º 20 (14 de outubro de 2022): 6076. http://dx.doi.org/10.3390/jcm11206076.
Texto completo da fonteSamadzadega, F., e H. Hasani. "DETERMINATION OF OPTIMUM CLASSIFICATION SYSTEM FOR HYPERSPECTRAL IMAGERY AND LIDAR DATA BASED ON BEES ALGORITHM". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (11 de dezembro de 2015): 651–56. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-651-2015.
Texto completo da fonteHatakeyama, Takao. "Associations between Autistic-like Traits and Imagery Ability". Vision 8, n.º 1 (12 de março de 2024): 13. http://dx.doi.org/10.3390/vision8010013.
Texto completo da fonteYang, Lingbo, Lamin Mansaray, Jingfeng Huang e Limin Wang. "Optimal Segmentation Scale Parameter, Feature Subset and Classification Algorithm for Geographic Object-Based Crop Recognition Using Multisource Satellite Imagery". Remote Sensing 11, n.º 5 (3 de março de 2019): 514. http://dx.doi.org/10.3390/rs11050514.
Texto completo da fonteChang, Hongli, e Jimin Yang. "Automated Selection of a Channel Subset Based on the Genetic Algorithm in a Motor Imagery Brain-Computer Interface System". IEEE Access 7 (2019): 154180–91. http://dx.doi.org/10.1109/access.2019.2944938.
Texto completo da fonteProbeck, Markus, Ralf Ludwig e Wolfram Mauser. "Fusion of NOAA-AVHRR imagery and geographical information system techniques to derive subscale land cover information for the upper Danube watershed". Hydrological Processes 19, n.º 12 (15 de agosto de 2005): 2407–18. http://dx.doi.org/10.1002/hyp.5892.
Texto completo da fonteWang, Yulei, Lin Wang, Hongye Xie e Chein-I. Chang. "Fusion of Various Band Selection Methods for Hyperspectral Imagery". Remote Sensing 11, n.º 18 (12 de setembro de 2019): 2125. http://dx.doi.org/10.3390/rs11182125.
Texto completo da fonteHoffman, Jay, Steven Ackerman, Yinghui Liu e Jeffrey Key. "The Detection and Characterization of Arctic Sea Ice Leads with Satellite Imagers". Remote Sensing 11, n.º 5 (4 de março de 2019): 521. http://dx.doi.org/10.3390/rs11050521.
Texto completo da fonteKiala, Zolo, Onisimo Mutanga, John Odindi e Kabir Peerbhay. "Feature Selection on Sentinel-2 Multispectral Imagery for Mapping a Landscape Infested by Parthenium Weed". Remote Sensing 11, n.º 16 (13 de agosto de 2019): 1892. http://dx.doi.org/10.3390/rs11161892.
Texto completo da fonteSafarov, Furkat, Kuchkorov Temurbek, Djumanov Jamoljon, Ochilov Temur, Jean Chamberlain Chedjou, Akmalbek Bobomirzaevich Abdusalomov e Young-Im Cho. "Improved Agricultural Field Segmentation in Satellite Imagery Using TL-ResUNet Architecture". Sensors 22, n.º 24 (13 de dezembro de 2022): 9784. http://dx.doi.org/10.3390/s22249784.
Texto completo da fonteKheira, Djelloul, e M. Beladgham. "Performance of channel selection used for Multi-class EEG signal classification of motor imagery". Indonesian Journal of Electrical Engineering and Computer Science 15, n.º 3 (1 de setembro de 2019): 1305. http://dx.doi.org/10.11591/ijeecs.v15.i3.pp1305-1312.
Texto completo da fonteMonsma, Eva V., e Lynnette Y. Overby. "The Relationship between Imagery and Competitive Anxiety in Ballet Auditions". Journal of Dance Medicine & Science 8, n.º 1 (março de 2004): 11–18. http://dx.doi.org/10.1177/1089313x0400800102.
Texto completo da fonteYassine, H., K. Tout e M. Jaber. "IMPROVING LULC CLASSIFICATION FROM SATELLITE IMAGERY USING DEEP LEARNING – EUROSAT DATASET". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (28 de junho de 2021): 369–76. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-369-2021.
Texto completo da fonteAbadal, Saüc, Luis Salgueiro, Javier Marcello e Verónica Vilaplana. "A Dual Network for Super-Resolution and Semantic Segmentation of Sentinel-2 Imagery". Remote Sensing 13, n.º 22 (12 de novembro de 2021): 4547. http://dx.doi.org/10.3390/rs13224547.
Texto completo da fonteHari Krishna, D., I. A.Pasha e T. Satya Savithri. "Multiclass classification of motor imagery EEG signals using ensemble classifiers & cross-correlation". International Journal of Engineering & Technology 7, n.º 2.6 (11 de março de 2018): 163. http://dx.doi.org/10.14419/ijet.v7i2.6.10144.
Texto completo da fonteAkay, A. E., B. Gencal e İ. Taş. "SPATIOTEMPORAL CHANGE DETECTION USING LANDSAT IMAGERY: THE CASE STUDY OF KARACABEY FLOODED FOREST, BURSA, TURKEY". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W4 (13 de novembro de 2017): 31–35. http://dx.doi.org/10.5194/isprs-annals-iv-4-w4-31-2017.
Texto completo da fonteMeyer, J., D. Rettenmund e S. Nebiker. "LONG-TERM VISUAL LOCALIZATION IN LARGE SCALE URBAN ENVIRONMENTS EXPLOITING STREET LEVEL IMAGERY". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (3 de agosto de 2020): 57–63. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-57-2020.
Texto completo da fonteChen, Buo-Fu, Boyo Chen, Hsuan-Tien Lin e Russell L. Elsberry. "Estimating Tropical Cyclone Intensity by Satellite Imagery Utilizing Convolutional Neural Networks". Weather and Forecasting 34, n.º 2 (1 de abril de 2019): 447–65. http://dx.doi.org/10.1175/waf-d-18-0136.1.
Texto completo da fonteAthanasiou, Alkinoos, Nikos Terzopoulos, Niki Pandria, Ioannis Xygonakis, Nicolas Foroglou, Konstantinos Polyzoidis e Panagiotis D. Bamidis. "Functional Brain Connectivity during Multiple Motor Imagery Tasks in Spinal Cord Injury". Neural Plasticity 2018 (2018): 1–20. http://dx.doi.org/10.1155/2018/9354207.
Texto completo da fonteDuarte-Carvajalino, Julio Martin, Elías Alexander Silva-Arero, Gerardo Antonio Góez-Vinasco, Laura Marcela Torres-Delgado, Oscar Dubán Ocampo-Paez e Angela María Castaño-Marín. "Estimation of Water Stress in Potato Plants Using Hyperspectral Imagery and Machine Learning Algorithms". Horticulturae 7, n.º 7 (2 de julho de 2021): 176. http://dx.doi.org/10.3390/horticulturae7070176.
Texto completo da fonteAngel, Yoseline, Rasmus Houborg e Matthew F. McCabe. "Reconstructing Cloud Contaminated Pixels Using Spatiotemporal Covariance Functions and Multitemporal Hyperspectral Imagery". Remote Sensing 11, n.º 10 (14 de maio de 2019): 1145. http://dx.doi.org/10.3390/rs11101145.
Texto completo da fonteLewandowski, Wendy, Ann Jacobson, Patrick A. Palmieri, Thomas Alexander e Richard Zeller. "Biological Mechanisms Related to the Effectiveness of Guided Imagery for Chronic Pain". Biological Research For Nursing 13, n.º 4 (26 de novembro de 2010): 364–75. http://dx.doi.org/10.1177/1099800410386475.
Texto completo da fonteAstiti, Sagung Putri Chandra, Takahiro Osawa e I. Wayan Nuarsa. "IDENTIFICATION OF SHORELINE CHANGES USING SENTINEL 2 IMAGERY DATA IN CANGGU COASTAL AREA". ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) 13, n.º 2 (30 de novembro de 2019): 191. http://dx.doi.org/10.24843/ejes.2019.v13.i02.p07.
Texto completo da fonteMoradi, F., A. Zarei, S. Ranjbar e S. Homayouni. "WHEAT BIOMASS ESTIMATION FROM UAV IMAGERY USING AN ENSEMBLE LEARNING APPROACH WITH BAYESIAN OPTIMIZATION". ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W1-2022 (14 de janeiro de 2023): 515–22. http://dx.doi.org/10.5194/isprs-annals-x-4-w1-2022-515-2023.
Texto completo da fonteDobrinić, D., M. Gašparović e D. Medak. "EVALUATION OF FEATURE SELECTION METHODS FOR VEGETATION MAPPING USING MULTITEMPORAL SENTINEL IMAGERY". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2022 (30 de maio de 2022): 485–91. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2022-485-2022.
Texto completo da fonteSedlak, René, Andreas Welscher, Patrick Hannawald, Sabine Wüst, Rainer Lienhart e Michael Bittner. "Analysis of 2D airglow imager data with respect to dynamics using machine learning". Atmospheric Measurement Techniques 16, n.º 12 (26 de junho de 2023): 3141–53. http://dx.doi.org/10.5194/amt-16-3141-2023.
Texto completo da fonteFeng, Ruyi, Lizhe Wang e Yanfei Zhong. "Least Angle Regression-Based Constrained Sparse Unmixing of Hyperspectral Remote Sensing Imagery". Remote Sensing 10, n.º 10 (25 de setembro de 2018): 1546. http://dx.doi.org/10.3390/rs10101546.
Texto completo da fonteWiniwarter, Lukas, Nicholas C. Coops, Alex Bastyr, Jean-Romain Roussel, Daisy Q. R. Zhao, Clayton T. Lamb e Adam T. Ford. "Extraction of Forest Road Information from CubeSat Imagery Using Convolutional Neural Networks". Remote Sensing 16, n.º 6 (20 de março de 2024): 1083. http://dx.doi.org/10.3390/rs16061083.
Texto completo da fonteLv, Chengzhe, Yuefeng Lu, Miao Lu, Xinyi Feng, Huadan Fan, Changqing Xu e Lei Xu. "A Classification Feature Optimization Method for Remote Sensing Imagery Based on Fisher Score and mRMR". Applied Sciences 12, n.º 17 (2 de setembro de 2022): 8845. http://dx.doi.org/10.3390/app12178845.
Texto completo da fonteImangholiloo, Mohammad, Ville Luoma, Markus Holopainen, Mikko Vastaranta, Antti Mäkeläinen, Niko Koivumäki, Eija Honkavaara e Ehsan Khoramshahi. "A New Approach for Feeding Multispectral Imagery into Convolutional Neural Networks Improved Classification of Seedlings". Remote Sensing 15, n.º 21 (3 de novembro de 2023): 5233. http://dx.doi.org/10.3390/rs15215233.
Texto completo da fonteSekandari, Milad, e Amin Beiranvand Pour. "Fuzzy Logic Modeling for Integrating the Thematic Layers Derived from Remote Sensing Imagery: A Mineral Exploration Technique". Environmental Sciences Proceedings 6, n.º 1 (25 de fevereiro de 2021): 8. http://dx.doi.org/10.3390/iecms2021-09349.
Texto completo da fonteKhare, Siddhartha, Hooman Latifi, Sergio Rossi e Sanjay Kumar Ghosh. "Fractional Cover Mapping of Invasive Plant Species by Combining Very High-Resolution Stereo and Multi-Sensor Multispectral Imageries". Forests 10, n.º 7 (27 de junho de 2019): 540. http://dx.doi.org/10.3390/f10070540.
Texto completo da fonteChen, Nian, Kezhong Lu e Hao Zhou. "A Search Method for Optimal Band Combination of Hyperspectral Imagery Based on Two Layers Selection Strategy". Computational Intelligence and Neuroscience 2021 (22 de junho de 2021): 1–14. http://dx.doi.org/10.1155/2021/5592323.
Texto completo da fonte