Relevant bibliographies by topics / Bunch graph

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Bunch graph'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Bunch graph"

1

Wiskott, Laurenz, Rolf Würtz, and Günter Westphal. "Elastic Bunch Graph Matching." Scholarpedia 9, no. 3 (2014): 10587. http://dx.doi.org/10.4249/scholarpedia.10587.

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Kwon, Mann-Jun, Hyoun-Joo Go, and Myung-Geun Chun. "Face Recognition using Fuzzy-EBGM(Elastic Bunch Graph Matching) Method." Journal of Korean Institute of Intelligent Systems 15, no. 6 (2005): 759–64. http://dx.doi.org/10.5391/jkiis.2005.15.6.759.

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Nandhini. "A STUDY ON TRIMODALDEPENDENCY GRAPH FORSOFTWARE CLUSTERING." IJCSET 2, no. 1 (2016): 10–17. https://doi.org/10.9091/zenodo.5574889.

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<strong>ABSTRACT</strong>- Software clustering is the process of combining multiple systems or applications into a cluster that act as a single system. The subsystems are reverse engineered to extract design data. When large software systems are reverse-engineered&nbsp;there is the possibility of the system decomposition&nbsp;hierarchy. Bunch&rsquo;s software clustering tool shows how meta-heuristic search algorithms&nbsp;can be applied to the software clustering problem, successfully. But some uncertainty prevails whether Bunch provide the optimal&nbsp;solution. The optimal solution for trivi
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Wiskott, L., J. M. Fellous, N. Kuiger, and C. von der Malsburg. "Face recognition by elastic bunch graph matching." IEEE Transactions on Pattern Analysis and Machine Intelligence 19, no. 7 (1997): 775–79. http://dx.doi.org/10.1109/34.598235.

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Bhat, Farooq Ahmad, and M. Arif Wani. "Elastic Bunch Graph Matching Based Face Recognition Under Varying Lighting, Pose, and Expression Conditions." IAES International Journal of Artificial Intelligence (IJ-AI) 3, no. 4 (2016): 177. http://dx.doi.org/10.11591/ijai.v3.i4.pp177-182.

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In this paper performance of elastic bunch graph matching (EBGM) for face recognition under variation in facial expression, variation in lighting condition and variation in poses are given. In this approach faces are represented by labelled graphs. Experimental results of EBGM on ORL, Yale B and FERET datasets are provided. Strong and weak features of EBGM algorithm are discussed.
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Heri Purwanto and Ika Ucha P.Rangkuti. "PENGUKURAN KUANTITAS UAP MASUK REBUSAN SECARA TIDAK LANGSUNG MENGGUNAKAN GRAFIK ROTOTHERM." Jurnal Agro Fabrica 2, no. 2 (2021): 58–65. http://dx.doi.org/10.47199/jaf.v2i2.125.

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Sterilization process is one of the keys to success in a Palm Oil Mill. In conventional palm oil mills that usehorizontal serilization, the fruit is heated in a closed vessel using pressurized steam at a pressure of 40 psiand a temperature of 140oC. The performance parameters that determine the success of the process inintermediate sterilization are pressure, temperature and time as well as steam requirements. This study aimsto determine the correlation between the area under sterilization graph represent the measurement of timeand pressure from every cycle of sterilization to oil losses in th
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Himanshu, Sharma*, Pawar Anand, Chourasia Chandhrvardan, and Khatri Sushma. "IMPLEMENTATION OF FACE RECOGNITION SYSTEM BASED ON ELASTIC BUNCH GRAPH MATCHING." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 3 (2016): 888–95. https://doi.org/10.5281/zenodo.48386.

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The face is regarded as the primary means of identifying the person of a written document based on the implicit assumption that a person&rsquo;s face changes slowly and is very difficult to erase, alter or forge without detection. As face is now a days the primary mechanism both for authentication and authorization in legal transactions, the need for efficient automated solutions for face reorganization has increased. This Project offers algorithm for the offline image reorganization system in which artificial neural network is used to confirm the genuineness of faces. We approach the problem
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Chithambarathanu, M., and D. R. Ganesh. "Data Clustering using Genomic Analysis in Graph model." Journal of Physics: Conference Series 2161, no. 1 (2022): 012029. http://dx.doi.org/10.1088/1742-6596/2161/1/012029.

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Abstract In the event that the data is addressed as a diagram, wherein the hubs are devices and the hyperlinks establish associations among devices then a bunch might be defined as an associated perspective; i.e., a gathering of devices that are identified with each other, yet that don’t have any association with objects outside the gathering. Bunching is an essential test in the quality examination. This ponders monster impact genetic field. Thusly in the current system, the various genomic assessments are scattered in various dispersed structures. In our proposed work, we endeavour to develo
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Chikkalingaiah, Anitha Arekattedoddi, Shrinivasa Naika Chikkathore Palya Laxmana, and Krishna Alabujanahalli Neelegowda. "Graph Cut Segmentation and Watershed Algorithm for Yield Count of an Arecanut Bunch." Ingénierie des systèmes d information 29, no. 6 (2024): 2425–31. https://doi.org/10.18280/isi.290629.

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Yang, Boyu, Weiguo Zheng, Xiang Lian, Yuzheng Cai, and X. Sean Wang. "HERO: A Hierarchical Set Partitioning and Join Framework for Speeding up the Set Intersection Over Graphs." Proceedings of the ACM on Management of Data 2, no. 1 (2024): 1–25. http://dx.doi.org/10.1145/3639284.

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As one of the most primitive operators in graph algorithms, such as the triangle counting, maximal clique enumeration, and subgraph listing, a set intersection operator returns common vertices between any two given sets of vertices in data graphs. It is therefore very important to accelerate the set intersection, which will benefit a bunch of tasks that take it as a built-in block. Existing works on the set intersection usually followed the merge intersection or galloping-search framework, and most optimization research focused on how to leverage the SIMD hardware instructions. In this paper,
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Dissertations / Theses on the topic "Bunch graph"

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Lin, Frank Chi-Hao. "Super-resolution image processing with application to face recognition." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/16703/1/Frank_Lin_Thesis.pdf.

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Subject identification from surveillance imagery has become an important task for forensic investigation. Good quality images of the subjects are essential for the surveillance footage to be useful. However, surveillance videos are of low resolution due to data storage requirements. In addition, subjects typically occupy a small portion of a camera's field of view. Faces, which are of primary interest, occupy an even smaller array of pixels. For reliable face recognition from surveillance video, there is a need to generate higher resolution images of the subject's face from low-resolution vide
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Lin, Frank Chi-Hao. "Super-resolution image processing with application to face recognition." Queensland University of Technology, 2008. http://eprints.qut.edu.au/16703/.

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Subject identification from surveillance imagery has become an important task for forensic investigation. Good quality images of the subjects are essential for the surveillance footage to be useful. However, surveillance videos are of low resolution due to data storage requirements. In addition, subjects typically occupy a small portion of a camera's field of view. Faces, which are of primary interest, occupy an even smaller array of pixels. For reliable face recognition from surveillance video, there is a need to generate higher resolution images of the subject's face from low-resolution vide
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Brink, Jan-Cor (Johannes Cornelius). "Quantification of spray coverage on grape bunch parts and the incidence of Botrytis cinerea." Thesis, Stellenbosch : Stellenbosch University, 2005. http://hdl.handle.net/10019.1/20915.

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Thesis (MScAgric)--University of Stellenbosch, 2005.<br>ENGLISH ABSTRACT: Various studies revealed that Botrytis cinerea, the causal pathogen of Botrytis bunch rot, is mostly associated with pedicels, rachises, laterals and berry bases, and not with berry skins as previously understood. Provided that sufficient coverage of inner bunch parts was achieved, laboratory studies have shown that fungicides can effectively reduce the amount of B. cinerea at the various positions in bunches, and prevent infection and symptom expression at all growth stages. The same efficacy was, however, not achi
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Moffat, Tessa. "Sensor technology to assess grape bunch temperature variability in Vitis vinifera L. cv. Shiraz." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80102.

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Thesis (MScAgric)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: The microclimate environment around the bunch is complex. The spatial distribution of leaves as well as bunch position and morphology impact on the path of direct radiation received by the berries. Canopy microclimate is largely determined by the meteorological conditions (air temperature, solar radiation, wind speed and direction, relative humidity, and precipitation) as well as management practices (trellis/training system, canopy height, vine spacing, row orientation, canopy management practices, irrigation and soil vari
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Engelbrecht, Rene. "The role of the mediterranean fruit fly, Ceratitis capitata, in Botrytis bunch rot of grape." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/53168.

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Thesis (MScAgric)--University of Stellenbosch, 2002.<br>ENGLISH ABSTRACT: Botrytis bunch rot of grape is caused by Botrytis cinerea Pers. :Fr. Conidia of the pathogen, which is dispersed by wind, water droplets and by insects, can penetrate the intact grape berry cuticle, but disease expression occurs only under predisposing conditions. Since relatively high infection rates often occur in vineyards, predisposing factors must play a fundamental role in primary infection and subsequent disease occurrence. Insects can play a very important role in this regard by depositing inocula at wound
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Capps, Eric R. "The Relationship Between Mineral Nutrition and Late-Season Bunch Stem Necrosis of Cabernet Sauvignon (Vitis vinifera L.) Grapevines." Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/31800.

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Late-season Bunch Stem Necrosis (BSN) is observed as a necrosis of the cluster stem (rachis) that leads to shriveling of berries on the affected portion of the cluster. Field experiments were conducted over three years at two vineyards in northern Virginia to examine relationships between specific nutrients and the incidence of BSN of Cabernet Sauvignon grapevines. Nutrients, used alone or in combination, included nitrogen, magnesium, and calcium. During the 1997 and 1998 seasons at Leesburg vineyard, applications of nitrogen, magnesium, and calcium produced little change in bloom-time peti
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Arlitsch, Kenning. "Semantic Web Identity of academic organizations." Doctoral thesis, Humboldt-Universität zu Berlin, Philosophische Fakultät I, 2017. http://dx.doi.org/10.18452/17671.

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Semantic Web Identity kennzeichnet den Zustand, in dem ein Unternehmen von Suchmaschinen als Solches erkannt wird. Das Abrufen einer Knowledge Graph Card in Google-Suchergebnissen für eine akademische Organisation wird als Indikator für SWI nominiert, da es zeigt, dass Google nachprüfbare Tatsachen gesammelt hat, um die Organisation als Einheit zu etablieren. Diese Anerkennung kann wiederum die Relevanz ihrer Verweisungen an diese Organisation verbessern. Diese Dissertation stellt Ergebnisse einer Befragung der 125 Mitgliedsbibliotheken der Association of Research Libraries vor. Die Ergebniss
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Sarkar, Sayantan, and Subhradeep Kayal. "Face Detection and Recognition using Skin Segmentation and Elastic Bunch Graph Matching." Thesis, 2011. http://ethesis.nitrkl.ac.in/2293/1/thesis.pdf.

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Recently, face detection and recognition is attracting a lot of interest in areas such as network security, content indexing and retrieval, and video compression, because ‘people’ are the object of attention in a lot of video or images. To perform such real-time detection and recognition, novel algorithms are needed, which better current efficiencies and speeds. This project is aimed at developing an efficient algorithm for face detection and recognition. This project is divided into two parts, the detection of a face from a complex environment and the subsequent recognition by comparison. F
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Chou, Jung-Tsung, and 周榮宗. "Face Recognition System based on Active Appearance Model and Elastic Bunch Graph Matching." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/09042413260649964823.

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碩士<br>國立交通大學<br>電機學院電機與控制學程<br>101<br>Early face recognition algorithms used simple geometric features, like feature color, shape, and position etc., but the recognition process has now matured into a mathematical representations and matching processes. Face recognition can be used for both verification and identification. There are two predominant approaches to the face recognition problem: geometric (feature-base) and photometric (view-base). Among many different algorithms, Principal Components Analysis (PCA) related algorithms are the most popular method in face recognition field. Howe
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Pickering, Andrea Hilary. "Factors affecting the predisposition of 'Cabernet Sauvignon' grapevines (Vitis vinifera L.) to the physiological disorder, bunch stem necrosis : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Plant Physiology at Massey University, Palmerston North, New Zealand." 2006. http://hdl.handle.net/10179/1513.

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Bunch stem necrosis (BSN) is a physiological disorder in grapes. It results in shrivelled berries with poor quality attributes such that wine produced from grapes with high BSN incidence is of compromised quality. Past research has proposed many different hypotheses to explain the disorder. Literature indicates that conditions during certain stages of development may predispose berries to BSN but results are not consistent as to which stage is the critical one or which factors have the most impact. This study was designed to resolve these points of uncertainty. Treatments that either enhanced
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Books on the topic "Bunch graph"

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Johnson, Dennis A. Botrytis bunch rot of grape. Cooperative Extension, College of Agriculture & Home Economics, Washington State University, 1986.

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Boxing Fans Are a Very Cynical Bunch: Funny Boxing Graph Paper Great for Mathematics, Formulas, Sums and Drawing School Notes and Capturing Ideas, Grid Paper Pad, Drafting Paper, Quad Ruled 5x5-Cute Gifts for Boxing Lovers. Independently Published, 2020.

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Book chapters on the topic "Bunch graph"

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Wiskott, Laurenz, Jean-Marc Fellous, Norbert Krüger, and Christoph von der Malsburg. "Face recognition by elastic bunch graph matching." In Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63460-6_150.

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Wiskott, Laurenz, Jean-Marc Fellous, Nobert Krüger, and Christoph von der Malsburg. "Face Recognition by Elastic Bunch Graph Matching*†." In INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION. Routledge, 2022. http://dx.doi.org/10.1201/9780203750520-11.

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Sarkar, Sayantan. "Skin Segmentation Based Elastic Bunch Graph Matching for Efficient Multiple Face Recognition." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30157-5_4.

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Tripathi, Manish Madhav, Mohd Haroon, Minsa Jafar, and Mansi Jain. "Maxillofacial Surgery Using X-Ray Based Face Recognition by Elastic Bunch Graph Matching." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14834-7_18.

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Pickering, Andrea H., Ian J. Warrington, and David J. Woolley. "Physiological Disorders of Grape: Bunch Stem Necrosis and Early Bunch Stem Necrosis." In Horticultural Reviews. John Wiley & Sons, Inc., 2009. http://dx.doi.org/10.1002/9780470593776.ch7.

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Delić, Mersija, Fikreta Behmen, Semira Sefo, Pakeza Drkenda, Saša Matijašević, and Ana Mandić. "Effect of Pruning on Mechanical Composition of Bunch of Table Grape Varieties (Vitis Vinifera L.)." In 32nd Scientific-Expert Conference of Agriculture and Food Industry. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47467-5_8.

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Denman, Simon, Frank Lin, Vinod Chandran, Sridha Sridharan, and Clinton Fookes. "Improved Subject Identification in Surveillance Video Using Super-Resolution." In Multimedia Networking and Coding. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2660-7.ch011.

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The time consuming and labour intensive task of identifying individuals in surveillance video is often challenged by poor resolution and the sheer volume of stored video. Faces or identifying marks such as tattoos are often too coarse for direct matching by machine or human vision. Object tracking and super-resolution can then be combined to facilitate the automated detection and enhancement of areas of interest. The object tracking process enables the automatic detection of people of interest, greatly reducing the amount of data for super-resolution. Smaller regions such as faces can also be
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Conference papers on the topic "Bunch graph"

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Hanmandlu, Madasu, Divya Gupta, and Shantaram Vasikarla. "Face recognition using Elastic bunch graph matching." In 2013 IEEE Applied Imagery Pattern Recognition Workshop: Sensing for Control and Augmentation (AIPR 2013). IEEE, 2013. http://dx.doi.org/10.1109/aipr.2013.6749338.

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Ejbali, Ridha, Mourad Zaied, and Chokri Ben Amar. "Face recognition based on Beta 2D Elastic Bunch Graph Matching." In 2013 13th International Conference on Hybrid Intelligent Systems (HIS). IEEE, 2013. http://dx.doi.org/10.1109/his.2013.6920461.

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Senaratne, Rajinda, and Saman Halgamuge. "Using Particle Swarm Optimisation for Elastic Bunch Graph Matching to Recognise Faces." In TENCON 2005 - 2005 IEEE Region 10 Conference. IEEE, 2005. http://dx.doi.org/10.1109/tencon.2005.301026.

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Chen, Xianming, Chaoyang Zhang, Fan Dong, and Zhaoxian Zhou. "Parallelization of elastic bunch graph matching (EBGM) algorithm for fast face recognition." In 2013 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP). IEEE, 2013. http://dx.doi.org/10.1109/chinasip.2013.6625328.

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Caceres, Juan Carlos Gutierrez, and Jose Rodrigo Galdos Chavez. "Modifications on illumination, distance function and Gabor masks for elastic bunch graph matching." In 2016 35th International Conference of the Chilean Computer Science Society (SCCC). IEEE, 2016. http://dx.doi.org/10.1109/sccc.2016.7836050.

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Xue-fang, Lv, and Ping Tao. "Realization of face recognition system based on Gabor wavelet and elastic bunch graph matching." In 2013 25th Chinese Control and Decision Conference (CCDC). IEEE, 2013. http://dx.doi.org/10.1109/ccdc.2013.6561532.

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Paria, Edison, Rolando Cardenas, Juan Gutierrez, and Jose Galdos. "An Improved Face Recognition Based on Illumination Normalization Techniques and Elastic Bunch Graph Matching." In the International Conference. ACM Press, 2017. http://dx.doi.org/10.1145/3093241.3093249.

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Chen, Xianming, Chaoyang Zhang, and Zhaoxian Zhou. "Improve recognition performance by hybridizing principal component analysis (PCA) and elastic bunch graph matching (EBGM)." In 2014 IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision Processing (CIMSIVP). IEEE, 2014. http://dx.doi.org/10.1109/cimsivp.2014.7013270.

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Gao, Lianli, Jingkuan Song, Dongxiang Zhang, and Heng Tao Shen. "Coarse-to-fine Image Co-segmentation with Intra and Inter Rank Constraints." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/100.

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Image co-segmentation is the problem of automatically discovering the common objects co-occurring in a set of relevant images and segmenting them as foreground simultaneously. Although a bunch of approaches have been proposed to address this problem, many of them still suffer from certain limitations, e.g., supervised feature learning and complex models, which hinder their capability in the real-world scenarios. To alleviate these limitations, we propose a novel coarse-to-fine co-segmentation (CFC) framework, which utilizes the coarse foreground and background proposals to learn a robust simil
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Mazumdar, D., K. Chanda, M. Bhattacharya, and S. Mitra. "A Pose Recovery Algorithm to Minimize the Effects of Pose Variation on the Matching Performance of Elastic Bunch Graph Based Multiview Face Recognition System." In 2007 International Conference on Computing: Theory and Applications (ICCTA'07). IEEE, 2007. http://dx.doi.org/10.1109/iccta.2007.18.

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Reports on the topic "Bunch graph"

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Reisch, Bruce, Pinhas Spiegel-Roy, Norman Weeden, Gozal Ben-Hayyim, and Jacques Beckmann. Genetic Analysis in vitis Using Molecular Markers. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7613014.bard.

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Genetic analysis and mapping in grapes has been difficult because of the long generation period and paucity of genetic markers. In the present work, chromosome linkage maps were developed with RAPD, RFLP and isozyme loci in interspecific hybrid cultivars, and RAPD markers were produced in a V. vinifera population. In three cultivars, there were 19 linkage groups as expected for a species with 38 somatic chromosomes. These maps were used to locate chromosome regions with linkages to important genes, including those influencing powdery mildew and botrytis bunch rot resistance; flower sex; and be
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