Zeitschriftenartikel zum Thema „Segmentation des pores“
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 "Segmentation des pores" 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.
Sintorn, Ida-Maria, Stina Svensson, Maria Axelsson und Gunilla Borgefors. „Segmentation of individual pores in 3D paper images“. Nordic Pulp & Paper Research Journal 20, Nr. 3 (01.08.2005): 316–19. http://dx.doi.org/10.3183/npprj-2005-20-03-p316-319.
Der volle Inhalt der QuelleBauer, Benjamin, Xiaohao Cai, Stephan Peth, Katja Schladitz und Gabriele Steidl. „Variational-based segmentation of bio-pores in tomographic images“. Computers & Geosciences 98 (Januar 2017): 1–8. http://dx.doi.org/10.1016/j.cageo.2016.09.013.
Der volle Inhalt der QuelleLiu, Lei, Qiaoling Han, Yue Zhao und Yandong Zhao. „A Novel Method Combining U-Net with LSTM for Three-Dimensional Soil Pore Segmentation Based on Computed Tomography Images“. Applied Sciences 14, Nr. 8 (16.04.2024): 3352. http://dx.doi.org/10.3390/app14083352.
Der volle Inhalt der QuelleYosifov, Miroslav, Patrick Weinberger, Bernhard Plank, Bernhard Fröhler, Markus Hoeglinger, Johann Kastner und Christoph Heinzl. „Segmentation of pores in carbon fiber reinforced polymers using the U-Net convolutional neural network“. Acta Polytechnica CTU Proceedings 42 (12.10.2023): 87–93. http://dx.doi.org/10.14311/app.2023.42.0087.
Der volle Inhalt der QuelleTomažinčič, Dejan, Žiga Virk, Peter Marijan Kink, Gregor Jerše und Jernej Klemenc. „Predicting the Fatigue Life of an AlSi9Cu3 Porous Alloy Using a Vector-Segmentation Technique for a Geometric Parameterisation of the Macro Pores“. Metals 11, Nr. 1 (31.12.2020): 72. http://dx.doi.org/10.3390/met11010072.
Der volle Inhalt der QuelleTong, Tong, Yan Cai, Da Wei Sun und Peng Liu. „Automatic Segmentation of Pores in Weld Images Based on Transition Region Extraction“. Applied Mechanics and Materials 217-219 (November 2012): 1964–67. http://dx.doi.org/10.4028/www.scientific.net/amm.217-219.1964.
Der volle Inhalt der QuelleYoon, Huisu, Semin Kim, Jongha Lee und Sangwook Yoo. „Deep-Learning-Based Morphological Feature Segmentation for Facial Skin Image Analysis“. Diagnostics 13, Nr. 11 (29.05.2023): 1894. http://dx.doi.org/10.3390/diagnostics13111894.
Der volle Inhalt der QuelleSong, Wenlong, Junyu Li, Kexin Li, Jingxu Chen und Jianping Huang. „An Automatic Method for Stomatal Pore Detection and Measurement in Microscope Images of Plant Leaf Based on a Convolutional Neural Network Model“. Forests 11, Nr. 9 (01.09.2020): 954. http://dx.doi.org/10.3390/f11090954.
Der volle Inhalt der QuelleSoboleva, N. N., und A. N. Mushnikov. „Determination of the volume fraction of primary carbides in the microstructure of composite coatings using semantic segmentation“. Frontier materials & technologies, Nr. 3 (2023): 95–102. http://dx.doi.org/10.18323/2782-4039-2023-3-65-9.
Der volle Inhalt der QuelleWen, Hao, Chang Huang und Shengmin Guo. „The Application of Convolutional Neural Networks (CNNs) to Recognize Defects in 3D-Printed Parts“. Materials 14, Nr. 10 (15.05.2021): 2575. http://dx.doi.org/10.3390/ma14102575.
Der volle Inhalt der QuelleLingnau, Lars A., Johannes Heermant, Johannes L. Otto, Kai Donnerbauer, Lukas M. Sauer, Lukas Lücker, Marina Macias Barrientos und Frank Walther. „Separation of Damage Mechanisms in Full Forward Rod Extruded Case-Hardening Steel 16MnCrS5 Using 3D Image Segmentation“. Materials 17, Nr. 12 (20.06.2024): 3023. http://dx.doi.org/10.3390/ma17123023.
Der volle Inhalt der QuelleLIN, WEI, XIZHE LI, ZHENGMING YANG, LIJUN LIN, SHENGCHUN XIONG, ZHIYUAN WANG, XIANGYANG WANG und QIANHUA XIAO. „A NEW IMPROVED THRESHOLD SEGMENTATION METHOD FOR SCANNING IMAGES OF RESERVOIR ROCKS CONSIDERING PORE FRACTAL CHARACTERISTICS“. Fractals 26, Nr. 02 (April 2018): 1840003. http://dx.doi.org/10.1142/s0218348x18400030.
Der volle Inhalt der QuelleDevi, M. Shyamala, A. N. Sruthi und P. Balamurugan. „Artificial neural network classification-based skin cancer detection“. International Journal of Engineering & Technology 7, Nr. 1.1 (21.12.2017): 591. http://dx.doi.org/10.14419/ijet.v7i1.1.10364.
Der volle Inhalt der QuelleVan Eyndhoven, G., M. Kurttepeli, C. J. Van Oers, P. Cool, S. Bals, K. J. Batenburg und J. Sijbers. „Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials“. Ultramicroscopy 148 (Januar 2015): 10–19. http://dx.doi.org/10.1016/j.ultramic.2014.08.008.
Der volle Inhalt der QuelleBraakman, Sietse T., A. Thomas Read, Darren W. H. Chan, C. Ross Ethier und Darryl R. Overby. „Colocalization of outflow segmentation and pores along the inner wall of Schlemm's canal“. Experimental Eye Research 130 (Januar 2015): 87–96. http://dx.doi.org/10.1016/j.exer.2014.11.008.
Der volle Inhalt der QuelleTang, Xin, Ruiyu He, Biao Wang, Yuerong Zhou und Hong Yin. „Intelligent Identification and Quantitative Characterization of Pores in Shale SEM Images Based on Pore-Net Deep-Learning Network Model“. Petrophysics – The SPWLA Journal of Formation Evaluation and Reservoir Description 65, Nr. 2 (01.04.2024): 233–45. http://dx.doi.org/10.30632/pjv65n2-2024a6.
Der volle Inhalt der QuelleBáez, Francisco, Álvaro A. Camargo und Gustavo D. A. Gastal. „Ultrastructural Imaging Analysis of the Zona Pellucida Surface in Bovine Oocytes“. Microscopy and Microanalysis 25, Nr. 4 (28.05.2019): 1032–36. http://dx.doi.org/10.1017/s1431927619000692.
Der volle Inhalt der QuelleBondarev, A. V., E. T. Zhilyakova, N. B. Demina und V. Y. Novikov. „Study of Morphology of Sorption Substances“. Drug development & registration 8, Nr. 2 (30.05.2019): 33–37. http://dx.doi.org/10.33380/2305-2066-2019-8-2-33-37.
Der volle Inhalt der QuelleHeylen, Rob, Aditi Thanki, Dries Verhees, Domenico Iuso, Jan De Beenhouwer, Jan Sijbers, Ann Witvrouw, Han Haitjema und Abdellatif Bey-Temsamani. „3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts“. Measurement Science and Technology 33, Nr. 4 (07.01.2022): 045602. http://dx.doi.org/10.1088/1361-6501/ac459a.
Der volle Inhalt der QuelleZHU, QINGYONG, WEIBIN YANG und HUAIZHONG YU. „STUDY ON THE PERMEABILITY OF RED SANDSTONE VIA IMAGE ENHANCEMENT“. Fractals 25, Nr. 06 (21.11.2017): 1750055. http://dx.doi.org/10.1142/s0218348x17500554.
Der volle Inhalt der QuelleHwang, Heesu, Dohyoung Kim, Yoonmi Nam, Jong-Ho Lee und Jin-Ha Hwang. „Synergistic Application of Machine Learning to Microstructural Characterization on Electrode Composites of Solid Oxide Fuel Cells“. ECS Transactions 111, Nr. 6 (19.05.2023): 445–51. http://dx.doi.org/10.1149/11106.0445ecst.
Der volle Inhalt der QuelleFu, Yinkai, Yue Zhao, Yandong Zhao und Qiaoling Han. „Semi-supervised segmentation of multi-scale soil pores based on a novel receptive field structure“. Computers and Electronics in Agriculture 212 (September 2023): 108071. http://dx.doi.org/10.1016/j.compag.2023.108071.
Der volle Inhalt der QuelleSuo, Limin, Zhaowei Wang, Hailong Liu, Likai Cui, Xianda Sun und Xudong Qin. „Innovative Deep Learning Approaches for High-Precision Segmentation and Characterization of Sandstone Pore Structures in Reservoirs“. Applied Sciences 14, Nr. 16 (15.08.2024): 7178. http://dx.doi.org/10.3390/app14167178.
Der volle Inhalt der QuelleZhao, Xinli, Zhengming Yang, Xuewei Liu, Zhiyuan Wang und Yutian Luo. „Analysis of pore throat characteristics of tight sandstone reservoirs“. Open Geosciences 12, Nr. 1 (12.10.2020): 977–89. http://dx.doi.org/10.1515/geo-2020-0121.
Der volle Inhalt der QuelleZhao, Jiang Kun, Yu Zhu und Jian Feng Yu. „Segmentation by Local Binary Fitting Active Contour Model for Activated Carbon Fibers Material Microscopic Images“. Advanced Materials Research 811 (September 2013): 370–74. http://dx.doi.org/10.4028/www.scientific.net/amr.811.370.
Der volle Inhalt der QuellePan, Shen, und Mineichi Kudo. „Segmentation of pores in wood microscopic images based on mathematical morphology with a variable structuring element“. Computers and Electronics in Agriculture 75, Nr. 2 (Februar 2011): 250–60. http://dx.doi.org/10.1016/j.compag.2010.11.010.
Der volle Inhalt der QuelleŻak, Andrzej M., Anna Wieczorek, Agnieszka Chowaniec und Łukasz Sadowski. „Segmentation of pores within concrete-epoxy interface using synchronous chemical composition mapping and backscattered electron imaging“. Measurement 206 (Januar 2023): 112334. http://dx.doi.org/10.1016/j.measurement.2022.112334.
Der volle Inhalt der QuelleLu, Yangchun, Ting Lu, Yudong Lu, Bo Wang, Guanghao Zeng und Xu Zhang. „The Study on Solving Large Pore Heat Transfer Simulation in Malan Loess Based on Volume Averaging Method Combined with CT Scan Images“. Sustainability 15, Nr. 16 (15.08.2023): 12389. http://dx.doi.org/10.3390/su151612389.
Der volle Inhalt der QuelleTkachev, Sergey, Natalia Chepelova, Gevorg Galechyan, Boris Ershov, Danila Golub, Elena Popova, Artem Antoshin et al. „Three-Dimensional Cell Culture Micro-CT Visualization within Collagen Scaffolds in an Aqueous Environment“. Cells 13, Nr. 15 (23.07.2024): 1234. http://dx.doi.org/10.3390/cells13151234.
Der volle Inhalt der QuelleFager, Andrew, Hiroshi Otomo, Rafael Salazar-Tio, Ganapathi Balasubramanian, Bernd Crouse, Raoyang Zhang, Hudong Chen und Josephina Schembre-McCabe. „Multi-scale Digital Rock: Application of a multi-scale multi-phase workflow to a Carbonate reservoir rock“. E3S Web of Conferences 366 (2023): 01001. http://dx.doi.org/10.1051/e3sconf/202336601001.
Der volle Inhalt der QuellePramana, A. A., G. Riantomo, A. P. Oktaviani, I. Setiabudi, F. D. E. Latief und M. A. Gibrata. „Digital Rock Physics Application in Determining The Porosity of Shale Rock“. Journal of Physics: Conference Series 2243, Nr. 1 (01.06.2022): 012021. http://dx.doi.org/10.1088/1742-6596/2243/1/012021.
Der volle Inhalt der QuelleZhang, Hao, Hewen Liu und Jinyong Bai. „Research on image recognition method of rock and soil porous media based on dithering algorithm“. E3S Web of Conferences 283 (2021): 01025. http://dx.doi.org/10.1051/e3sconf/202128301025.
Der volle Inhalt der QuelleHu, Zhazha, Rui Zhang, Kai Zhu, Dongyin Li, Yi Jin, Wenbing Guo, Xiao Liu, Xiaodong Zhang und Qian Zhang. „Probing the Pore Structure of the Berea Sandstone by Using X-ray Micro-CT in Combination with ImageJ Software“. Minerals 13, Nr. 3 (04.03.2023): 360. http://dx.doi.org/10.3390/min13030360.
Der volle Inhalt der QuelleScott, Sarah, Wei-Ying Chen und Alexander Heifetz. „Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals“. Sensors 23, Nr. 20 (14.10.2023): 8462. http://dx.doi.org/10.3390/s23208462.
Der volle Inhalt der QuelleHan, Yubo, und Ye Liu. „Intelligent Classification and Segmentation of Sandstone Thin Section Image Using a Semi-Supervised Framework and GL-SLIC“. Minerals 14, Nr. 8 (05.08.2024): 799. http://dx.doi.org/10.3390/min14080799.
Der volle Inhalt der QuelleBondarev, Alexander, Elena Zhilyakova, Anastasia Malyutina, Larissa Kozubova, Natalia Avtina, Elena Timoshenko und Georgy Vasiliev. „Structural features of mineral carriers of medicinal substances“. BIO Web of Conferences 40 (2021): 03007. http://dx.doi.org/10.1051/bioconf/20214003007.
Der volle Inhalt der QuelleXavier, Matheus S., Sam Yang, Christophe Comte, Alireza Bab-Hadiashar, Neil Wilson und Ivan Cole. „Nondestructive quantitative characterisation of material phases in metal additive manufacturing using multi-energy synchrotron X-rays microtomography“. International Journal of Advanced Manufacturing Technology 106, Nr. 5-6 (10.12.2019): 1601–15. http://dx.doi.org/10.1007/s00170-019-04597-y.
Der volle Inhalt der QuelleXiao, Xiaoling, Jiarui Zhang, Xinyu Li, Jing Zhang und Xiang Zhang. „Study on Extraction Methods for Different Components in a Carbonate Digital Core“. Mathematical Problems in Engineering 2020 (07.09.2020): 1–6. http://dx.doi.org/10.1155/2020/8972494.
Der volle Inhalt der QuelleSong, Meihui, Yue Zhao, Yandong Zhao und Qiaoling Han. „ACFTransUNet: A new multi-category soil pores 3D segmentation model combining Transformer and CNN with concentrated-fusion attention“. Computers and Electronics in Agriculture 225 (Oktober 2024): 109312. http://dx.doi.org/10.1016/j.compag.2024.109312.
Der volle Inhalt der QuelleIdowu, N. A. A., C. Nardi, H. Long, T. Varslot und P. E. E. Øren. „Effects of Segmentation and Skeletonization Algorithms on Pore Networks and Predicted Multiphase-Transport Properties of Reservoir-Rock Samples“. SPE Reservoir Evaluation & Engineering 17, Nr. 04 (13.08.2014): 473–83. http://dx.doi.org/10.2118/166030-pa.
Der volle Inhalt der QuelleNemati, Saber, Hamed Ghadimi, Xin Li, Leslie G. Butler, Hao Wen und Shengmin Guo. „Automated Defect Analysis of Additively Fabricated Metallic Parts Using Deep Convolutional Neural Networks“. Journal of Manufacturing and Materials Processing 6, Nr. 6 (13.11.2022): 141. http://dx.doi.org/10.3390/jmmp6060141.
Der volle Inhalt der QuelleAditya Putra Prananda, A. M. H. Pardede und Rahmadani. „Segmentation Algorithm K – Means Based On The Maturity Level Of Blueberries“. Journal of Artificial Intelligence and Engineering Applications (JAIEA) 3, Nr. 2 (15.02.2024): 584–89. http://dx.doi.org/10.59934/jaiea.v3i2.433.
Der volle Inhalt der QuelleOjeda-Magaña, B., J. Quintanilla-Domínguez, R. Ruelas, L. Gómez Barba und D. Andina. „Improvement of the Image Sub-Segmentation for Identification and Differentiation of Atypical Regions“. International Journal of Pattern Recognition and Artificial Intelligence 32, Nr. 01 (09.10.2017): 1860011. http://dx.doi.org/10.1142/s021800141860011x.
Der volle Inhalt der QuelleZhang, Jingmin. „Reversible Data Hiding of Digital Image Based on Pixel Combination Algorithm“. Advances in Multimedia 2022 (15.07.2022): 1–11. http://dx.doi.org/10.1155/2022/8627056.
Der volle Inhalt der QuelleC Mohammed Gulzar, Et al. „Survey on Therapy Prediction using Deep Learning for Pores and Skin Diseases“. International Journal on Recent and Innovation Trends in Computing and Communication 11, Nr. 10 (02.11.2023): 1429–34. http://dx.doi.org/10.17762/ijritcc.v11i10.8687.
Der volle Inhalt der QuelleZhang, Feng, Ghislain Bournival, Hamed Lamei Ramandi und Seher Ata. „Digital Cake Analysis: A Novel Coal Filter Cake Examination Technique Using Microcomputed Tomography“. Minerals 13, Nr. 12 (30.11.2023): 1509. http://dx.doi.org/10.3390/min13121509.
Der volle Inhalt der QuelleSilva, Miquéias A. S., Susana M. Iglesias, Paulo E. Ambrosio, Iram B. R. Ortiz, Dany S. Dominguez und Diego Frias. „Application of Segmentation and Fuzzy Classification Techniques (TSK) in Analyzing the Composition of Lightweight Concretes Containing Ethylene Vinyl Acetate and Natural Fibers Using Micro-Computed Tomography Images“. Applied Sciences 14, Nr. 1 (28.12.2023): 296. http://dx.doi.org/10.3390/app14010296.
Der volle Inhalt der QuellePeng, Jiayi, Zhenzhong Shen und Jiafa Zhang. „Measuring the Effect of Pack Shape on Gravel’s Pore Characteristics and Permeability Using X-ray Diffraction Computed Tomography“. Materials 15, Nr. 17 (05.09.2022): 6173. http://dx.doi.org/10.3390/ma15176173.
Der volle Inhalt der QuelleBallóková, Beáta, Marián Lázár, Natália Jasminská, Zuzana Molčanová, Štefan Michalik, Tomáš Brestovič, Jozef Živčák und Karol Saksl. „Development and Testing of Copper Filters for Efficient Application in Half-Face Masks“. Applied Sciences 12, Nr. 13 (05.07.2022): 6824. http://dx.doi.org/10.3390/app12136824.
Der volle Inhalt der QuelleŻak, Andrzej M., Anna Wieczorek, Agnieszka Chowaniec und Łukasz Sadowski. „Segmentation of pores in cementitious materials based on backscattered electron measurements: A new proposal of regression-based approach for threshold estimation“. Construction and Building Materials 368 (März 2023): 130419. http://dx.doi.org/10.1016/j.conbuildmat.2023.130419.
Der volle Inhalt der Quelle