Literatura científica selecionada sobre o tema "Classification/segmentation"
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Artigos de revistas sobre o assunto "Classification/segmentation"
Levner, Ilya, e Hong Zhang. "Classification-Driven Watershed Segmentation". IEEE Transactions on Image Processing 16, n.º 5 (maio de 2007): 1437–45. http://dx.doi.org/10.1109/tip.2007.894239.
Texto completo da fontePavlidis, Theo, e Jiangying Zhou. "Page segmentation and classification". CVGIP: Graphical Models and Image Processing 54, n.º 6 (novembro de 1992): 484–96. http://dx.doi.org/10.1016/1049-9652(92)90068-9.
Texto completo da fonteKhanykov, I. G. "Classification of image segmentation algorithms". Izvestiâ vysših učebnyh zavedenij. Priborostroenie 61, n.º 11 (30 de novembro de 2018): 978–87. http://dx.doi.org/10.17586/0021-3454-2018-61-11-978-987.
Texto completo da fonteWang, Ying, Jie Su, Qiuyu Xu e Yixin Zhong. "A Collaborative Learning Model for Skin Lesion Segmentation and Classification". Diagnostics 13, n.º 5 (28 de fevereiro de 2023): 912. http://dx.doi.org/10.3390/diagnostics13050912.
Texto completo da fonteSekhar, Mr Ch, Ms A. Sharmila, Mr Ch Narayana, Mr A. Rutwick, Mr B. Srinu, Mr D. Pramod Kumar e Mr B. Snehith. "Osteoporosis Diagnosis through Visual Segmentation and Classification: Extensive Review". International Journal of Research Publication and Reviews 5, n.º 3 (9 de março de 2024): 3748–53. http://dx.doi.org/10.55248/gengpi.5.0324.0771.
Texto completo da fonteHyun-Cheol Park, Hyun-Cheol Park, Raman Ghimire Hyun-Cheol Park, Sahadev Poudel Raman Ghimire e Sang-Woong Lee Sahadev Poudel. "Deep Learning for Joint Classification and Segmentation of Histopathology Image". 網際網路技術學刊 23, n.º 4 (julho de 2022): 903–10. http://dx.doi.org/10.53106/160792642022072304025.
Texto completo da fontePandeya, Yagya Raj, Bhuwan Bhattarai e Joonwhoan Lee. "Tracking the Rhythm: Pansori Rhythm Segmentation and Classification Methods and Datasets". Applied Sciences 12, n.º 19 (23 de setembro de 2022): 9571. http://dx.doi.org/10.3390/app12199571.
Texto completo da fonteVohra, Sumit K., e Dimiter Prodanov. "The Active Segmentation Platform for Microscopic Image Classification and Segmentation". Brain Sciences 11, n.º 12 (14 de dezembro de 2021): 1645. http://dx.doi.org/10.3390/brainsci11121645.
Texto completo da fonteAbbas, Khamael, e Mustafa Rydh. "Satellite Image Classification and Segmentation by Using JSEG Segmentation Algorithm". International Journal of Image, Graphics and Signal Processing 4, n.º 10 (17 de setembro de 2012): 48–53. http://dx.doi.org/10.5815/ijigsp.2012.10.07.
Texto completo da fonteMittal, Praveen, e Charul Bhatnagar. "Detection of DME by Classification and Segmentation Using OCT Images". Webology 19, n.º 1 (20 de janeiro de 2022): 601–12. http://dx.doi.org/10.14704/web/v19i1/web19043.
Texto completo da fonteTeses / dissertações sobre o assunto "Classification/segmentation"
Porter, Robert Mark Stefan. "Texture classification and segmentation". Thesis, University of Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389032.
Texto completo da fonteTan, Tieniu. "Image texture analysis : classification and segmentation". Thesis, Imperial College London, 1990. http://hdl.handle.net/10044/1/8697.
Texto completo da fonteWong, Jennifer L. "A material segmentation and classification system". Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85523.
Texto completo da fonteCataloged from PDF version of thesis.
Includes bibliographical references (page 75).
In this thesis, I developed a material segmentation and classification system that takes in images of an object and identifies the material composition of the object's surface. The 3D surface is first segmented into regions that likely contain the same material, using color as a heuristic measure. The material classification of each region is then based on the cosine lobe model. The cosine lobe model is our adopted reflectance model, which allows for a simple approximation of a material's reflectance properties, which then serves as the material's unique signature.
by Jennifer L. Wong.
M. Eng.
Anusha, Anusha. "Word Segmentation for Classification of Text". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-396969.
Texto completo da fonteLotz, Max. "Depth Inclusion for Classification and Semantic Segmentation". Thesis, KTH, Robotik, perception och lärande, RPL, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233371.
Texto completo da fonteMajoriteten av algoritmerna för datorseende använder bara färginformation för att dra sultsatser om hur världen ser ut. Med ökande tillgänglighet av RGB-D-kameror är det viktigt att undersöka sätt att effektivt kombinera färg- med djupinformation. I denna uppsats undersöks hur djup kan kombineras med färg i CNN:er för att öka presentandan i både klassificering och semantisk segmentering, så väl som att undersöka hur djupet kodas mest effektivt före dess inkludering i nätverket. Att lägga till djupet som en fjärde färgkanal och modifiera en förtränad CNN utreds inledningsvis. Sedan studeras att istället skapa en separat kopia av nätverket för att träna djup och sedan kombinera utdata från båda nätverken. Resultatet visar att det är ineffektivt att lägga till djup som en fjärde färgkanal då nätverket begränsas av den sämsta informationen från djup och färg. Fusion från två separata nätverk med färg och djup ökar prestanda bortom det som färg och djup erbjuder separat. Resultatet visar också att metoder så som HHA-kodning, är överlägsna jämfört med enklare transformationer så som HSV. Värt att notera är att detta endast gäller då djupbilderna är normaliserade över alla bilders maxdjup och inte i varje enskild bilds för sig. Motsatsen är sann för enklare transformationer.
Arcila, Romain. "Séquences de maillages : classification et méthodes de segmentation". Phd thesis, Université Claude Bernard - Lyon I, 2011. http://tel.archives-ouvertes.fr/tel-00653542.
Texto completo da fonteTress, Andrew. "Practical classification and segmentation of large textural images". Thesis, Heriot-Watt University, 1996. http://hdl.handle.net/10399/720.
Texto completo da fonteShaffrey, Cian William. "Multiscale techniques for image segmentation, classification and retrieval". Thesis, University of Cambridge, 2003. https://www.repository.cam.ac.uk/handle/1810/272033.
Texto completo da fonteKühne, Gerald. "Motion based segmentation and classification of video objects". [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10605031.
Texto completo da fonteTóvári, Dániel. "Segmentation Based Classification of Airborne Laser Scanner Data". [S.l. : s.n.], 2006. http://digbib.ubka.uni-karlsruhe.de/volltexte/1000006285.
Texto completo da fonteLivros sobre o assunto "Classification/segmentation"
Sithole, George. Segmentation and classification of airborne laser scanner data. Delft: Nederlandse Commissie voor Geodesie, 2005.
Encontre o texto completo da fonteCharters, Graham Castree. Segmentation and classification in automated chromosome analysis using trainable models. Manchester: University of Manchester, 1994.
Encontre o texto completo da fonteShusharina, Nadya, Mattias P. Heinrich e Ruobing Huang, eds. Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71827-5.
Texto completo da fonteMoukadem, Ali, Djaffar Ould Abdeslam e Alain Dieterlen. Time-Frequency Domain for Segmentation and Classification of Non-Stationary Signals. Hoboken, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118908686.
Texto completo da fonteK, Kokula Krishna Hari, ed. An Image Segmentation and Classification for Brain Tumor Detection using Pillar K-Means Algorithm. Chennai, India: Association of Scientists, Developers and Faculties, 2016.
Encontre o texto completo da fonteAbkar, Ali Akbar. Likelihood-based segmentation and classification of remotely sensed images: A Bayesian optimization approach for combining RS and GIS. Enschede, The Netherlands: International Institute for Aerospace Survey and Earth Sciences, 1999.
Encontre o texto completo da fonteAntonacopoulos, A. Page segmentation and classification using the description of the background: A flexible and efficient approach for documents with complex and traditional layouts. Manchester: UMIST, 1995.
Encontre o texto completo da fonteAfanas'ev, Mihail, Mihail Bendikov e Stanislav Korunov. Fundamentals of the economy of space activities. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1018193.
Texto completo da fonteIntelmann, Steven S. Automated, objective texture segmentation of multibeam echosounder data: Seafloor survey and substrate maps from James Island to Ozette Lake, Washington outer coast. Silver Spring, Md: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, National Marine Sanctuary Program, 2007.
Encontre o texto completo da fonteSuri, Jasjit S., e Ayman S. El-Baz. Artificial Intelligence Strategies for Brain Tumor Diagnosis: Segmentation and Classification Strategies in MRI. Elsevier Science & Technology Books, 2023.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Classification/segmentation"
Gale, Shawn. "Segmentation and Classification". In Encyclopedia of Clinical Neuropsychology, 3104–5. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_9062.
Texto completo da fonteGale, Shawn D. "Segmentation and Classification". In Encyclopedia of Clinical Neuropsychology, 1–2. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_9062-2.
Texto completo da fontePietikäinen, Matti, Abdenour Hadid, Guoying Zhao e Timo Ahonen. "Texture Classification and Segmentation". In Computational Imaging and Vision, 69–79. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-748-8_4.
Texto completo da fonteChapman, Chris, e Elea McDonnell Feit. "Segmentation: Clustering and Classification". In R for Marketing Research and Analytics, 299–338. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14436-8_11.
Texto completo da fonteChapman, Chris, e Elea McDonnell Feit. "Segmentation: Clustering and Classification". In Use R!, 299–340. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14316-9_11.
Texto completo da fonteAthanasiadis, Thanos, Phivos Mylonas, Georgios Th. Papadopoulos, Vasileios Mezaris, Yannis Avrithis, Ioannis Kompatsiaris e Michael G. Strintzis. "Knowledge-Driven Segmentation and Classification". In Multimedia Semantics, 163–81. Chichester, UK: John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119970231.ch10.
Texto completo da fonteHe, Jia, Chang-Su Kim e C. C. Jay Kuo. "Interactive Segmentation: Overview and Classification". In SpringerBriefs in Electrical and Computer Engineering, 7–16. Singapore: Springer Singapore, 2013. http://dx.doi.org/10.1007/978-981-4451-60-4_2.
Texto completo da fonteHati, Avik, Rajbabu Velmurugan, Sayan Banerjee e Subhasis Chaudhuri. "Co-segmentation Using a Classification Framework". In Image Co-segmentation, 123–49. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8570-6_6.
Texto completo da fonteWang, Yaping, Hongjun Jia, Pew-Thian Yap, Bo Cheng, Chong-Yaw Wee, Lei Guo e Dinggang Shen. "Groupwise Segmentation Improves Neuroimaging Classification Accuracy". In Multimodal Brain Image Analysis, 185–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33530-3_16.
Texto completo da fonteGong, Yang Can, Michael Brady e Styliani Petroudi. "Texture Based Mammogram Classification and Segmentation". In Digital Mammography, 616–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11783237_83.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Classification/segmentation"
Nowling, Ronald J., John Bukowy, Sean D. McGarry, Andrew S. Nencka, Oliver Blasko, Jay Urbain, Allison Lowman et al. "Classification before Segmentation: Improved U-Net Prostate Segmentation". In 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI). IEEE, 2019. http://dx.doi.org/10.1109/bhi.2019.8834494.
Texto completo da fonteLi, Xiaomin, Yuanyuan Wang, Yinhui Deng e Jinhua Yu. "Cell Segmentation Using Ellipse Curve Segmentation and Classification". In 2009 First International Conference on Information Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/icise.2009.381.
Texto completo da fonteJun Huang, Yuan Dong, Jiqing Liu, Chengyu Dong e Haila Wang. "Sports audio segmentation and classification". In 2009 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC 2009). IEEE, 2009. http://dx.doi.org/10.1109/icnidc.2009.5360872.
Texto completo da fonteKhoulqi, Ichrak, e Najlae Idrissi. "Segmentation and Classification of Cervical Cancer". In 2020 IEEE 6th International Conference on Optimization and Applications (ICOA). IEEE, 2020. http://dx.doi.org/10.1109/icoa49421.2020.9094517.
Texto completo da fonteMasood, N. A., H. M. Mashali e Abdalla S. A. Mohamed. "Color Segmentation for Skin Lesions Classification". In 2008 Cairo International Biomedical Engineering Conference (CIBEC). IEEE, 2008. http://dx.doi.org/10.1109/cibec.2008.4786059.
Texto completo da fonteKimball, Owen, Mari Ostendorf e Robin Rohlicek. "Recognition using classification and segmentation scoring". In the workshop. Morristown, NJ, USA: Association for Computational Linguistics, 1992. http://dx.doi.org/10.3115/1075527.1075570.
Texto completo da fonteKhoulqi, Ichrak, e Najlae Idrissi. "Breast cancer image segmentation and classification". In the 4th International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3368756.3369039.
Texto completo da fontePillai, Raji R., e Sumam Mary Idicula. "Linear text segmentation using classification techniques". In the 1st Amrita ACM-W Celebration. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1858378.1858436.
Texto completo da fonteCiftci, Cemalettin, Emrah Ergul e Nafiz Arica. "Scene classification using saliency based segmentation". In 2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU). IEEE, 2011. http://dx.doi.org/10.1109/siu.2011.5929766.
Texto completo da fonteLo, Pechin, e Marleen de Bruijne. "Voxel classification based airway tree segmentation". In Medical Imaging, editado por Joseph M. Reinhardt e Josien P. W. Pluim. SPIE, 2008. http://dx.doi.org/10.1117/12.772777.
Texto completo da fonteRelatórios de organizações sobre o assunto "Classification/segmentation"
Kimball, Owen, Mari Ostendorf e Robin Rohlicek. Recognition Using Classification and Segmentation Scoring. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1992. http://dx.doi.org/10.21236/ada457477.
Texto completo da fonteOkun, Oleg, David Doermann e Matti Pietikainen. Page Segmentation and Zone Classification: The State of the Art. Fort Belvoir, VA: Defense Technical Information Center, novembro de 1999. http://dx.doi.org/10.21236/ada458676.
Texto completo da fonteLecumberry, Federico, Alvaro Pardo e Guillermo Sapiro. Simultaneous Object Classification and Segmentation with High-Order Multiple Shape Models. Fort Belvoir, VA: Defense Technical Information Center, maio de 2009. http://dx.doi.org/10.21236/ada513239.
Texto completo da fonteMarroquin, Jose L., e Federico Girosi. Some Extensions of the K-Means Algorithm for Image Segmentation and Pattern Classification. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1993. http://dx.doi.org/10.21236/ada271691.
Texto completo da fonteAlhasson, Haifa F., e Shuaa S. Alharbi. New Trends in image-based Diabetic Foot Ucler Diagnosis Using Machine Learning Approaches: A Systematic Review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, novembro de 2022. http://dx.doi.org/10.37766/inplasy2022.11.0128.
Texto completo da fonteAsari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan e Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), dezembro de 2015. http://dx.doi.org/10.55274/r0010891.
Texto completo da fonteCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li e Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Texto completo da fonteCheng, Peng, James V. Krogmeier, Mark R. Bell, Joshua Li e Guangwei Yang. Detection and Classification of Concrete Patches by Integrating GPR and Surface Imaging. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317320.
Texto completo da fonteHodgdon, Taylor, Anthony Fuentes, Jason Olivier, Brian Quinn e Sally Shoop. Automated terrain classification for vehicle mobility in off-road conditions. Engineer Research and Development Center (U.S.), abril de 2021. http://dx.doi.org/10.21079/11681/40219.
Texto completo da fonte