Literatura académica sobre el tema "Scale Invariant Feature Descriptor"
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Artículos de revistas sobre el tema "Scale Invariant Feature Descriptor"
Sahan, Ali Sahan, Nisreen Jabr, Ahmed Bahaaulddin y Ali Al-Itb. "Human identification using finger knuckle features". International Journal of Advances in Soft Computing and its Applications 14, n.º 1 (28 de marzo de 2022): 88–101. http://dx.doi.org/10.15849/ijasca.220328.07.
Texto completoXu, Xinggui, Ping Yang, Bing Ran, Hao Xian y Yong Liu. "Long-distance deformation object recognition by integrating contour structure and scale-invariant heat kernel signature". Journal of Intelligent & Fuzzy Systems 39, n.º 3 (7 de octubre de 2020): 3241–57. http://dx.doi.org/10.3233/jifs-191649.
Texto completoDiaz-Escobar, Julia, Vitaly Kober y Jose A. Gonzalez-Fraga. "LUIFT: LUminance Invariant Feature Transform". Mathematical Problems in Engineering 2018 (28 de octubre de 2018): 1–17. http://dx.doi.org/10.1155/2018/3758102.
Texto completoEl Chakik, Abdallah, Abdul Rahman El Sayed, Hassan Alabboud y Amer Bakkach. "An invariant descriptor map for 3D objects matching". International Journal of Engineering & Technology 9, n.º 1 (23 de enero de 2020): 59. http://dx.doi.org/10.14419/ijet.v9i1.29918.
Texto completoAjayi, O. G. "PERFORMANCE ANALYSIS OF SELECTED FEATURE DESCRIPTORS USED FOR AUTOMATIC IMAGE REGISTRATION". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (21 de agosto de 2020): 559–66. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-559-2020.
Texto completoTikhomirova, T. A., G. T. Fedorenko, K. M. Nazarenko y E. S. Nazarenko. "LEFT: LOCAL EDGE FEATURES TRANSFORM". Vestnik komp'iuternykh i informatsionnykh tekhnologii, n.º 189 (marzo de 2020): 11–18. http://dx.doi.org/10.14489/vkit.2020.03.pp.011-018.
Texto completoZhang, Wanyuan, Tian Zhou, Chao Xu y Meiqin Liu. "A SIFT-Like Feature Detector and Descriptor for Multibeam Sonar Imaging". Journal of Sensors 2021 (15 de julio de 2021): 1–14. http://dx.doi.org/10.1155/2021/8845814.
Texto completoGao, Junchai y Zhen Sun. "An Improved ASIFT Image Feature Matching Algorithm Based on POS Information". Sensors 22, n.º 20 (12 de octubre de 2022): 7749. http://dx.doi.org/10.3390/s22207749.
Texto completoBarajas-García, Carolina, Selene Solorza-Calderón y Everardo Gutiérrez-López. "Scale, translation and rotation invariant Wavelet Local Feature Descriptor". Applied Mathematics and Computation 363 (diciembre de 2019): 124594. http://dx.doi.org/10.1016/j.amc.2019.124594.
Texto completoFERRAZ, CAROLINA TOLEDO, OSMANDO PEREIRA, MARCOS VERDINI ROSA y ADILSON GONZAGA. "OBJECT RECOGNITION BASED ON BAG OF FEATURES AND A NEW LOCAL PATTERN DESCRIPTOR". International Journal of Pattern Recognition and Artificial Intelligence 28, n.º 08 (diciembre de 2014): 1455010. http://dx.doi.org/10.1142/s0218001414550106.
Texto completoTesis sobre el tema "Scale Invariant Feature Descriptor"
Emir, Erdem. "A Comparative Performance Evaluation Of Scale Invariant Interest Point Detectors For Infrared And Visual Images". Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12610159/index.pdf.
Texto completoHall, Daniela. "Viewpoint independent recognition of objects from local appearance". Grenoble INPG, 2001. http://www.theses.fr/2001INPG0086.
Texto completoKerr, Dermot. "Autonomous Scale Invariant Feature Extraction". Thesis, University of Ulster, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.502896.
Texto completoSaad, Elhusain Salem. "Defocus Blur-Invariant Scale-Space Feature Extractions". University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1418907974.
Texto completoShen, Yao. "Scene Analysis Using Scale Invariant Feature Extraction and Probabilistic Modeling". Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc84275/.
Texto completoZhang, Zheng y 张政. "Passivity assessment and model order reduction for linear time-invariant descriptor systems in VLSI circuit simulation". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44909056.
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Electrical and Electronic Engineering
Master
Master of Philosophy
Accordino, Andrea. "Studio e sviluppo di descrittori locali per nuvole di punti basati su proprietà geometriche". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17919/.
Texto completoLindeberg, Tony. "Scale Selection Properties of Generalized Scale-Space Interest Point Detectors". KTH, Beräkningsbiologi, CB, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-101220.
Texto completoQC 20121003
Image descriptors and scale-space theory for spatial and spatio-temporal recognition
May, Michael. "Data analytics and methods for improved feature selection and matching". Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/data-analytics-and-methods-for-improved-feature-selection-and-matching(965ded10-e3a0-4ed5-8145-2af7a8b5e35d).html.
Texto completoDecombas, Marc. "Compression vidéo très bas débit par analyse du contenu". Thesis, Paris, ENST, 2013. http://www.theses.fr/2013ENST0067/document.
Texto completoThe objective of this thesis is to find new methods for semantic video compatible with a traditional encoder like H.264/AVC. The main objective is to maintain the semantic and not the global quality. A target bitrate of 300 Kb/s has been fixed for defense and security applications. To do that, a complete chain of compression has been proposed. A study and new contributions on a spatio-temporal saliency model have been done to extract the important information in the scene. To reduce the bitrate, a resizing method named seam carving has been combined with the H.264/AVC encoder. Also, a metric combining SIFT points and SSIM has been created to measure the quality of objects without being disturbed by less important areas containing mostly artifacts. A database that can be used for testing the saliency model but also for video compression has been proposed, containing sequences with their manually extracted binary masks. All the different approaches have been thoroughly validated by different tests. An extension of this work on video summary application has also been proposed
Capítulos de libros sobre el tema "Scale Invariant Feature Descriptor"
Yue, Sicong, Qing Wang y Rongchun Zhao. "Robust Wide Baseline Feature Point Matching Based on Scale Invariant Feature Descriptor". En Lecture Notes in Computer Science, 329–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-87442-3_42.
Texto completoBanerjee, Biplab, Tanusree Bhattacharjee y Nirmalya Chowdhury. "Image Object Classification Using Scale Invariant Feature Transform Descriptor with Support Vector Machine Classifier with Histogram Intersection Kernel". En Information and Communication Technologies, 443–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15766-0_71.
Texto completoRahman, Md Mahmudur, Sameer K. Antani y George R. Thoma. "Biomedical Image Retrieval in a Fuzzy Feature Space with Affine Region Detection and Vector Quantization of a Scale-Invariant Descriptor". En Advances in Visual Computing, 261–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17277-9_27.
Texto completoKim, So Yeon, Yenewondim Biadgie y Kyung-Ah Sohn. "Investigating the Effectiveness of E-mail Spam Image Data for Phone Spam Image Detection Using Scale Invariant Feature Transform Image Descriptor". En Lecture Notes in Electrical Engineering, 591–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46578-3_69.
Texto completoGuo, Xiaojie, Xiaochun Cao, Jiawan Zhang y Xuewei Li. "MIFT: A Mirror Reflection Invariant Feature Descriptor". En Computer Vision – ACCV 2009, 536–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12304-7_50.
Texto completoBurger, Wilhelm y Mark J. Burge. "Scale-Invariant Feature Transform (SIFT)". En Texts in Computer Science, 609–64. London: Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-6684-9_25.
Texto completoBurger, Wilhelm y Mark J. Burge. "Scale-Invariant Feature Transform (SIFT)". En Texts in Computer Science, 709–63. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05744-1_25.
Texto completoGupta, Raj y Anurag Mittal. "SMD: A Locally Stable Monotonic Change Invariant Feature Descriptor". En Lecture Notes in Computer Science, 265–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88688-4_20.
Texto completoVardy, Andrew y Franz Oppacher. "A Scale Invariant Local Image Descriptor for Visual Homing". En Biomimetic Neural Learning for Intelligent Robots, 362–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11521082_22.
Texto completoEl-Mashad, Shady Y. y Amin Shoukry. "Towards a Robust Scale Invariant Feature Correspondence". En Lecture Notes in Computer Science, 33–43. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19941-2_4.
Texto completoActas de conferencias sobre el tema "Scale Invariant Feature Descriptor"
Chen, Qiu, Koji Kotani, Feifei Lee y Tadahiro Ohmi. "Scale-Invariant Feature Extraction by VQ-Based Local Image Descriptor". En 2008 International Conference on Computational Intelligence for Modelling Control & Automation. IEEE, 2008. http://dx.doi.org/10.1109/cimca.2008.134.
Texto completoHuang, Hui, Lizhong Lu, Bin Yan y Jian Chen. "A new scale invariant feature detector and modified SURF descriptor". En 2010 Sixth International Conference on Natural Computation (ICNC). IEEE, 2010. http://dx.doi.org/10.1109/icnc.2010.5583377.
Texto completoMiao, Jun, Jun Chu, Guimei Zhang y Ruina Feng. "A wide baseline matching method based on scale invariant feature descriptor". En Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, editado por Mingyue Ding, Bir Bhanu, Friedrich M. Wahl y Jonathan Roberts. SPIE, 2009. http://dx.doi.org/10.1117/12.832419.
Texto completoHindmarsh, Samuel, Peter Andreae y Mengjie Zhang. "Genetic programming for improving image descriptors generated using the scale-invariant feature transform". En the 27th Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2425836.2425855.
Texto completoGiles, C. Lee y Arthur D. Fisher. "Architecture for Optical Generation of Invariant Contour Features". En Machine Vision. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/mv.1985.thd6.
Texto completoOlszewska, J. I. y D. Wilson. "Hausdorff-distance enhanced matching of Scale Invariant Feature Transform descriptors in context of image querying". En 2012 IEEE 16th International Conference on Intelligent Engineering Systems (INES). IEEE, 2012. http://dx.doi.org/10.1109/ines.2012.6249809.
Texto completoSheng, Y. y H. H. Arsenault. "Invariant recognition using circular Fourier radial-mellin descriptors". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.the3.
Texto completoHu, Shuaizhou, Xinyao Zhang, Hao-yu Liao, Xiao Liang, Minghui Zheng y Sara Behdad. "Deep Learning and Machine Learning Techniques to Classify Electrical and Electronic Equipment". En ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/detc2021-71403.
Texto completoMoreno-Noguer, Francesc. "Deformation and illumination invariant feature point descriptor". En 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2011. http://dx.doi.org/10.1109/cvpr.2011.5995529.
Texto completoGeng, Z. X. y Y. Q. Qiao. "An Improved Illumination Invariant SURF Image Feature Descriptor". En 2017 International Conference on Virtual Reality and Visualization (ICVRV). IEEE, 2017. http://dx.doi.org/10.1109/icvrv.2017.00090.
Texto completoInformes sobre el tema "Scale Invariant Feature Descriptor"
Lei, Lydia. Three dimensional shape retrieval using scale invariant feature transform and spatial restrictions. Gaithersburg, MD: National Institute of Standards and Technology, 2009. http://dx.doi.org/10.6028/nist.ir.7625.
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