Zeitschriftenartikel zum Thema „Pixel-Object classification“
Geben Sie eine Quelle nach APA, MLA, Chicago, Harvard und anderen Zitierweisen an
Machen Sie sich mit Top-50 Zeitschriftenartikel für die Forschung zum Thema "Pixel-Object classification" bekannt.
Neben jedem Werk im Literaturverzeichnis ist die Option "Zur Bibliographie hinzufügen" verfügbar. Nutzen Sie sie, wird Ihre bibliographische Angabe des gewählten Werkes nach der nötigen Zitierweise (APA, MLA, Harvard, Chicago, Vancouver usw.) automatisch gestaltet.
Sie können auch den vollen Text der wissenschaftlichen Publikation im PDF-Format herunterladen und eine Online-Annotation der Arbeit lesen, wenn die relevanten Parameter in den Metadaten verfügbar sind.
Sehen Sie die Zeitschriftenartikel für verschiedene Spezialgebieten durch und erstellen Sie Ihre Bibliographie auf korrekte Weise.
Bernardini, A., E. Frontoni, E. S. Malinverni, A. Mancini, A. N. Tassetti und P. Zingaretti. „Pixel, object and hybrid classification comparisons“. Journal of Spatial Science 55, Nr. 1 (Juni 2010): 43–54. http://dx.doi.org/10.1080/14498596.2010.487641.
Der volle Inhalt der QuelleMakinde, Esther Oluwafunmilayo, Ayobami Taofeek Salami, James Bolarinwa Olaleye und Oluwapelumi Comfort Okewusi. „Object Based and Pixel Based Classification Using Rapideye Satellite Imager of ETI-OSA, Lagos, Nigeria“. Geoinformatics FCE CTU 15, Nr. 2 (08.12.2016): 59–70. http://dx.doi.org/10.14311/gi.15.2.5.
Der volle Inhalt der QuelleMartínez Prentice, Ricardo, Miguel Villoslada Peciña, Raymond D. Ward, Thaisa F. Bergamo, Chris B. Joyce und Kalev Sepp. „Machine Learning Classification and Accuracy Assessment from High-Resolution Images of Coastal Wetlands“. Remote Sensing 13, Nr. 18 (14.09.2021): 3669. http://dx.doi.org/10.3390/rs13183669.
Der volle Inhalt der QuelleLiu, Yanzhu, Yanan Wang und Adams Wai Kin Kong. „Pixel-wise ordinal classification for salient object grading“. Image and Vision Computing 106 (Februar 2021): 104086. http://dx.doi.org/10.1016/j.imavis.2020.104086.
Der volle Inhalt der QuelleHe, Ziqiang, Shaosheng Dai und Jinsong Liu. „Single-pixel object classification using ordered illumination patterns“. Optics Communications 573 (Dezember 2024): 131023. http://dx.doi.org/10.1016/j.optcom.2024.131023.
Der volle Inhalt der QuelleKang, Min Jo, Victor Mesev und Won Kyung Kim. „Measurements of Impervious Surfaces - per-pixel, sub-pixel, and object-oriented classification -“. Korean Journal of Remote Sensing 31, Nr. 4 (31.08.2015): 303–19. http://dx.doi.org/10.7780/kjrs.2015.31.4.3.
Der volle Inhalt der QuelleDeur, Martina, Mateo Gašparović und Ivan Balenović. „An Evaluation of Pixel- and Object-Based Tree Species Classification in Mixed Deciduous Forests Using Pansharpened Very High Spatial Resolution Satellite Imagery“. Remote Sensing 13, Nr. 10 (11.05.2021): 1868. http://dx.doi.org/10.3390/rs13101868.
Der volle Inhalt der QuelleEndo, Yutaka, und Gai Nakajima. „Compressive phase object classification using single-pixel digital holography“. Optics Express 30, Nr. 15 (15.07.2022): 28057. http://dx.doi.org/10.1364/oe.463395.
Der volle Inhalt der QuellePowar, Sudhir K., Sachin S. Panhalkar und Abhijit S. Patil. „An Evaluation of Pixel-based and Object-based Classification Methods for Land Use Land Cover Analysis Using Geoinformatic Techniques“. Geomatics and Environmental Engineering 16, Nr. 2 (09.02.2022): 61–75. http://dx.doi.org/10.7494/geom.2022.16.2.61.
Der volle Inhalt der QuelleTurissa, Pragunanti, Nababan Bisman, Siregar Vincentius, Kushardono Dony und Madduppa Hawis. „Evaluation Methods of Change Detection of Seagrass Beds in the Waters of Pajenekang and Gusung Selayar“. Trends in Sciences 18, Nr. 23 (15.11.2021): 677. http://dx.doi.org/10.48048/tis.2021.677.
Der volle Inhalt der QuelleAghababaei, Masoumeh, Ataollah Ebrahimi, Ali Asghar Naghipour, Esmaeil Asadi und Jochem Verrelst. „Classification of Plant Ecological Units in Heterogeneous Semi-Steppe Rangelands: Performance Assessment of Four Classification Algorithms“. Remote Sensing 13, Nr. 17 (29.08.2021): 3433. http://dx.doi.org/10.3390/rs13173433.
Der volle Inhalt der QuelleSong, M., D. L. Civco und J. D. Hurd. „A competitive pixel-object approach for land cover classification“. International Journal of Remote Sensing 26, Nr. 22 (20.11.2005): 4981–97. http://dx.doi.org/10.1080/01431160500213912.
Der volle Inhalt der QuelleDe Giglio, Michaela, Nicolas Greggio, Floriano Goffo, Nicola Merloni, Marco Dubbini und Maurizio Barbarella. „Comparison of Pixel- and Object-Based Classification Methods of Unmanned Aerial Vehicle Data Applied to Coastal Dune Vegetation Communities: Casal Borsetti Case Study“. Remote Sensing 11, Nr. 12 (14.06.2019): 1416. http://dx.doi.org/10.3390/rs11121416.
Der volle Inhalt der QuelleCoslu, M., N. K. Sonmez und D. Koc-San. „OBJECT-BASED GREENHOUSE CLASSIFICATION FROM HIGH RESOLUTION SATELLITE IMAGERY: A CASE STUDY ANTALYA-TURKEY“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (21.06.2016): 183–87. http://dx.doi.org/10.5194/isprs-archives-xli-b7-183-2016.
Der volle Inhalt der QuelleCoslu, M., N. K. Sonmez und D. Koc-San. „OBJECT-BASED GREENHOUSE CLASSIFICATION FROM HIGH RESOLUTION SATELLITE IMAGERY: A CASE STUDY ANTALYA-TURKEY“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (21.06.2016): 183–87. http://dx.doi.org/10.5194/isprsarchives-xli-b7-183-2016.
Der volle Inhalt der QuelleKarakus, P., und H. Karabork. „EFFECT OF PANSHARPENED IMAGE ON SOME OF PIXEL BASED AND OBJECT BASED CLASSIFICATION ACCURACY“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (21.06.2016): 235–39. http://dx.doi.org/10.5194/isprs-archives-xli-b7-235-2016.
Der volle Inhalt der QuelleKarakus, P., und H. Karabork. „EFFECT OF PANSHARPENED IMAGE ON SOME OF PIXEL BASED AND OBJECT BASED CLASSIFICATION ACCURACY“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (21.06.2016): 235–39. http://dx.doi.org/10.5194/isprsarchives-xli-b7-235-2016.
Der volle Inhalt der QuelleUbben, Niklas, Maren Pukrop und Thomas Jarmer. „Spatial Resolution as a Factor for Efficient UAV-Based Weed Mapping—A Soybean Field Case Study“. Remote Sensing 16, Nr. 10 (17.05.2024): 1778. http://dx.doi.org/10.3390/rs16101778.
Der volle Inhalt der QuelleJaber, Hussein Sabah, Muntadher Aidi Shareef und Zainab Fahkri Merzah. „OBJECT-BASED APPROACHES FOR LAND USE-LAND COVER CLASSIFICATION USING HIGH RESOLUTION QUICK BIRD SATELLITE IMAGERY (A CASE STUDY: KERBELA, IRAQ)“. Geodesy and cartography 48, Nr. 2 (29.06.2022): 85–91. http://dx.doi.org/10.3846/gac.2022.14453.
Der volle Inhalt der QuelleJi, X., und X. Niu. „The Attribute Accuracy Assessment of Land Cover Data in the National Geographic Conditions Survey“. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-4 (23.04.2014): 35–40. http://dx.doi.org/10.5194/isprsannals-ii-4-35-2014.
Der volle Inhalt der QuelleWu, Nitu, Luís Guilherme Teixeira Crusiol, Guixiang Liu, Deji Wuyun und Guodong Han. „Comparing Machine Learning Algorithms for Pixel/Object-Based Classifications of Semi-Arid Grassland in Northern China Using Multisource Medium Resolution Imageries“. Remote Sensing 15, Nr. 3 (28.01.2023): 750. http://dx.doi.org/10.3390/rs15030750.
Der volle Inhalt der QuelleQu, Le’an, Zhenjie Chen, Manchun Li, Junjun Zhi und Huiming Wang. „Accuracy Improvements to Pixel-Based and Object-Based LULC Classification with Auxiliary Datasets from Google Earth Engine“. Remote Sensing 13, Nr. 3 (28.01.2021): 453. http://dx.doi.org/10.3390/rs13030453.
Der volle Inhalt der QuelleVu Viet Du, Quan, Tam Minh Pham, Van Manh Pham, Huu Duy Nguyen, Quoc Huy Nguyen, Viet Thanh Pham und Huan Cao Nguyen. „An experimental comparison of pixel-based and object-based classifications with different machine learning algorithms in landscape pattern analysis – Case study from Quang Ngai city, Vietnam“. IOP Conference Series: Earth and Environmental Science 1345, Nr. 1 (01.05.2024): 012019. http://dx.doi.org/10.1088/1755-1315/1345/1/012019.
Der volle Inhalt der QuelleOthman, Ainon Nisa, Nurhanisah Hashim, Pauziyah Mohamad Salim und Puteri Norsarifah Suhada Mohd Zaidi. „Comparative Study of Pixel-Based and Object-Based Classifications in Benthic Mapping“. Journal of Advanced Geospatial Science & Technology 3, Nr. 2 (30.08.2023): 51–62. http://dx.doi.org/10.11113/jagst.v3n2.69.
Der volle Inhalt der QuelleSoffianian, Ali Reza, Neda Bihamta Toosi, Ali Asgarian, Hervé Regnauld, Sima Fakheran und Lars T. Waser. „Evaluating resampled and fused Sentinel-2 data and machine-learning algorithms for mangrove mapping in the northern coast of Qeshm island, Iran“. Nature Conservation 52 (20.03.2023): 1–22. http://dx.doi.org/10.3897/natureconservation.52.89639.
Der volle Inhalt der QuelleJia, Jie, Yong Jun Yang, Yi Ming Hou, Xiang Yang Zhang und He Huang. „Adaboost Classification-Based Object Tracking Method for Sequence Images“. Applied Mechanics and Materials 44-47 (Dezember 2010): 3902–6. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.3902.
Der volle Inhalt der QuelleLi, Gang, und Youchuan Wan. „A new combination classification of pixel- and object-based methods“. International Journal of Remote Sensing 36, Nr. 23 (23.11.2015): 5842–68. http://dx.doi.org/10.1080/01431161.2015.1109728.
Der volle Inhalt der QuelleCastillejo-González, Isabel. „Mapping of Olive Trees Using Pansharpened QuickBird Images: An Evaluation of Pixel- and Object-Based Analyses“. Agronomy 8, Nr. 12 (02.12.2018): 288. http://dx.doi.org/10.3390/agronomy8120288.
Der volle Inhalt der QuelleHadavand, Ahmad, Mehdi Mokhtarzadeh, Mohammad Javad Valadan Zoej, Saeid Homayouni und Mohammad Saadatseresht. „USING PIXEL-BASED AND OBJECT-BASED METHODS TO CLASSIFY URBAN HYPERSPECTRAL FEATURES“. Geodesy and cartography 42, Nr. 3 (22.09.2016): 92–105. http://dx.doi.org/10.3846/20296991.2016.1226388.
Der volle Inhalt der QuelleSefercik, U. G., T. Kavzoglu, I. Colkesen, S. Adali, S. Dinc, M. Nazar und M. Y. Ozturk. „LAND COVER CLASSIFICATION PERFORMANCE OF MULTISPECTRAL RTK UAVs“. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W5-2021 (23.12.2021): 489–92. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w5-2021-489-2021.
Der volle Inhalt der QuelleALİYU, Abdulazeez Onotu, Ebenezer Ayobami AKOMOLAFE, Adamu BALA, Terwase YOUNGU, Hassan MUSA und Swafiyudeen BAWA. „Integrated Method for Classifying Medium Resolution Satellite Remotely Sensed Imagery into Land Use Map“. International Journal of Environment and Geoinformatics 10, Nr. 2 (15.06.2023): 135–44. http://dx.doi.org/10.30897/ijegeo.1150436.
Der volle Inhalt der QuelleAlonso-Benito, Alfonso, Lara A. Arroyo, Manuel Arbelo, Pedro Hernández-Leal und Alejandro González-Calvo. „Pixel and object-based classification approaches for mapping forest fuel types in Tenerife Island from ASTER data“. International Journal of Wildland Fire 22, Nr. 3 (2013): 306. http://dx.doi.org/10.1071/wf11068.
Der volle Inhalt der QuelleXiao, Xingyuan, Linlong Jiang, Yaqun Liu und Guozhen Ren. „Limited-Samples-Based Crop Classification Using a Time-Weighted Dynamic Time Warping Method, Sentinel-1 Imagery, and Google Earth Engine“. Remote Sensing 15, Nr. 4 (17.02.2023): 1112. http://dx.doi.org/10.3390/rs15041112.
Der volle Inhalt der QuelleYao, Manhong, Shujun Zheng, Yuhang Hu, Zibang Zhang, Junzheng Peng und Jingang Zhong. „Single-Pixel Moving Object Classification with Differential Measuring in Transform Domain and Deep Learning“. Photonics 9, Nr. 3 (21.03.2022): 202. http://dx.doi.org/10.3390/photonics9030202.
Der volle Inhalt der QuelleHe, Shi, Hong Tang, Jing Li, Yang Shu und Li Shen. „Object-Oriented Semisupervised Classification of VHR Images by Combining MedLDA and a Bilateral Filter“. Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/182439.
Der volle Inhalt der QuelleCastillejo-González, Isabel, Cristina Angueira, Alfonso García-Ferrer und Manuel Sánchez de la Orden. „Combining Object-Based Image Analysis with Topographic Data for Landform Mapping: A Case Study in the Semi-Arid Chaco Ecosystem, Argentina“. ISPRS International Journal of Geo-Information 8, Nr. 3 (07.03.2019): 132. http://dx.doi.org/10.3390/ijgi8030132.
Der volle Inhalt der QuelleTroje, N. F., und T. Vetter. „Pixel-Based versus Correspondence-Based Representations of Human Faces: Implications for Sex Discrimination“. Perception 25, Nr. 1_suppl (August 1996): 161. http://dx.doi.org/10.1068/v96l1112.
Der volle Inhalt der QuelleYang, Qiu Xia, Chuan Wen Luo und Tian Kai Chen. „Remote Sensing Image Classification Based on Object-Oriented Method and Support Vector Machine: A Case Study in Harbin City“. Advanced Materials Research 912-914 (April 2014): 1331–34. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1331.
Der volle Inhalt der QuelleOuchra, Hafsa, Abdessamad Belangour und Allae Erraissi. „A Comparative Study on Pixel-based Classification and Object-Oriented Classification of Satellite Image“. International Journal of Engineering Trends and Technology 70, Nr. 8 (31.08.2022): 206–15. http://dx.doi.org/10.14445/22315381/ijett-v70i8p221.
Der volle Inhalt der QuelleBarzegar, M., H. Ebadi und A. Kiani. „COMPARISON OF DIFFERENT VEGETATION INDICES FOR VERY HIGH-RESOLUTION IMAGES, SPECIFIC CASE ULTRACAM-D IMAGERY“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1-W5 (10.12.2015): 97–104. http://dx.doi.org/10.5194/isprsarchives-xl-1-w5-97-2015.
Der volle Inhalt der QuelleEl-Ashmawy, N., A. Shaker und W. Yan. „PIXEL VS OBJECT-BASED IMAGE CLASSIFICATION TECHNIQUES FOR LIDAR INTENSITY DATA“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXVIII-5/W12 (03.09.2012): 43–48. http://dx.doi.org/10.5194/isprsarchives-xxxviii-5-w12-43-2011.
Der volle Inhalt der QuelleLi, Da, Haoxiang Chai, Qin Wei, Yao Zhang und Yunhan Xiao. „PACR: Pixel Attention in Classification and Regression for Visual Object Tracking“. Mathematics 11, Nr. 6 (14.03.2023): 1406. http://dx.doi.org/10.3390/math11061406.
Der volle Inhalt der QuelleZhang, Chi, Shiqing Wei, Shunping Ji und Meng Lu. „Detecting Large-Scale Urban Land Cover Changes from Very High Resolution Remote Sensing Images Using CNN-Based Classification“. ISPRS International Journal of Geo-Information 8, Nr. 4 (11.04.2019): 189. http://dx.doi.org/10.3390/ijgi8040189.
Der volle Inhalt der QuelleMahmoud, Ammar Shaker, Mustafa Ridha Mezaal, Mustafa Raad Hameed und Ahmed Samir Naje. „A Framework for Improving Urban Land Cover Using Object and Pixel-Based Techniques via Remotely Sensed Data“. Nature Environment and Pollution Technology 21, Nr. 5(Suppl) (29.12.2022): 2189–200. http://dx.doi.org/10.46488/nept.2022.v21i05.013.
Der volle Inhalt der QuelleNugroho, Jalu Tejo, Zylshal, Nurwita Mustika Sari und Dony Kushardono. „A COMPARISON OF OBJECT-BASED AND PIXEL-BASED APPROACHES FOR LAND USE/LAND COVER CLASSIFICATION USING LAPAN-A2 MICROSATELLITE DATA“. International Journal of Remote Sensing and Earth Sciences (IJReSES) 14, Nr. 1 (21.06.2017): 27. http://dx.doi.org/10.30536/j.ijreses.2017.v14.a2680.
Der volle Inhalt der QuelleMancera Florez, Juan Ricardo, und Ivan Alberto Lizarazo Salcedo. „Land cover classification at three different levels of detail from optical and radar Sentinel SAR data: a case study in Cundinamarca (Colombia)“. DYNA 87, Nr. 215 (05.11.2020): 136–45. http://dx.doi.org/10.15446/dyna.v87n215.84915.
Der volle Inhalt der QuelleShen, Xiaoqing, Megan K. Clayton, Michael J. Starek, Anjin Chang, Russell W. Jessup und Jamie L. Foster. „Identification of Brush Species and Herbicide Effect Assessment in Southern Texas Using an Unoccupied Aerial System (UAS)“. Remote Sensing 15, Nr. 13 (21.06.2023): 3211. http://dx.doi.org/10.3390/rs15133211.
Der volle Inhalt der QuelleSahu, R., und R. D. Gupta. „CONCEPTUAL FRAMEWORK OF COMBINED PIXEL AND OBJECT-BASED METHOD FOR DELINEATION OF DEBRIS-COVERED GLACIERS“. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5 (15.11.2018): 173–80. http://dx.doi.org/10.5194/isprs-annals-iv-5-173-2018.
Der volle Inhalt der QuelleBenazir Meerasha. „A Comparison of Pixel Based and Object Based Image Classification for Cropland Area Estimation“. Journal of Electrical Systems 20, Nr. 7s (04.05.2024): 2314–22. http://dx.doi.org/10.52783/jes.3967.
Der volle Inhalt der QuelleZhang, Y., K. Qin, C. Zeng, E. B. Zhang, M. X. Yue und X. Tong. „A DATA FIELD METHOD FOR URBAN REMOTELY SENSED IMAGERY CLASSIFICATION CONSIDERING SPATIAL CORRELATION“. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (21.06.2016): 431–35. http://dx.doi.org/10.5194/isprs-archives-xli-b7-431-2016.
Der volle Inhalt der Quelle