Relevant bibliographies by topics / Object-Based model

Contents

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

Academic literature on the topic 'Object-Based model'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Object-Based model"

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Biegelbauer, Georg, Markus Vincze, and Walter Wohlkinger. "Model-based 3D object detection." Machine Vision and Applications 21, no. 4 (2008): 497–516. http://dx.doi.org/10.1007/s00138-008-0178-3.

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Arumugam, Chamundeswari, and Chitra Babu. "Test Size Estimation for Object Oriented Software Based on Analysis Model." Journal of Software 10, no. 6 (2015): 713–29. http://dx.doi.org/10.17706//jsw.10.6.713-729.

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Qi Chen, Qi Chen, Xinyi Gao Qi Chen, Renjie Li Xinyi Gao, and Yong Zhang Renjie Li. "Optimized Object Detection Based on The Improved Lightweight Model Mini Net." 網際網路技術學刊 25, no. 2 (2024): 223–32. http://dx.doi.org/10.53106/160792642024032502005.

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<p>This paper proposes a Mini Net lightweight model that can be used for real-time detection. This model works together with Mini Lower and Mini Higher, which greatly improves the detection efficiency while ensuring the accuracy. The Mini module designs both the batch normalization layer and the excitation function at the front end of the module, which realizes efficient convolution, greatly reduces the amount of parameters and computation, and introduces the nonlinearity brought by more layers in the spatial dimension, which can improve the performance of the module extraction capacity.
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Bae, Je-Min. "Analogy-based Reuse of Object Model." KIPS Transactions:PartD 14D, no. 6 (2007): 665–74. http://dx.doi.org/10.3745/kipstd.2007.14-d.6.665.

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KIM, SUNGHO, GIJEONG JANG, WANG-HEON LEE, and IN SO KWEON. "COMBINED MODEL-BASED 3D OBJECT RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 19, no. 07 (2005): 839–52. http://dx.doi.org/10.1142/s0218001405004368.

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This paper presents a combined model-based 3D object recognition method motivated by the robust properties of human vision. The human visual system (HVS) is very efficient and robust in identifying and grabbing objects, in part because of its properties of visual attention, contrast mechanism, feature binding, multiresolution and part-based representation. In addition, the HVS combines bottom-up and top-down information effectively using combined model representation. We propose a method for integrating these aspects under a Monte Carlo method. In this scheme, object recognition is regarded as
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Lamdan, Y., J. T. Schwartz, and H. J. Wolfson. "Affine invariant model-based object recognition." IEEE Transactions on Robotics and Automation 6, no. 5 (1990): 578–89. http://dx.doi.org/10.1109/70.62047.

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Jang, Dae-Sik, Gye-Young Kim, and Hyung-Il Choi. "Model-based tracking of moving object." Pattern Recognition 30, no. 6 (1997): 999–1008. http://dx.doi.org/10.1016/s0031-3203(96)00128-8.

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UENO, Haruki, and Yasumasa OOMORI. "Expert Systems Based on Object Model." Geoinformatics 2, no. 2 (1991): 97–108. http://dx.doi.org/10.6010/geoinformatics1990.2.2_97.

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Jalila, A., and D. Jeya Mala. "Object-oriented model-based specification languages." ACM SIGSOFT Software Engineering Notes 39, no. 5 (2014): 1–4. http://dx.doi.org/10.1145/2659118.2659132.

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Nixon, D., and R. Lobb. "A fluid-based soft-object model." IEEE Computer Graphics and Applications 22, no. 4 (2002): 68–75. http://dx.doi.org/10.1109/mcg.2002.1016700.

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Dissertations / Theses on the topic "Object-Based model"

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Uluat, Mehmet Fatih. "Model-based Approach To The Federation Object Model Independence Problem." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/3/12608672/index.pdf.

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One of the promises of High Level Architecture (HLA) is the reusability of simulation components. Although HLA supports reusability to some extent with mechanisms provided by Object Model Template (OMT), when the developer wants to use an existing federate application within another federation with a different Federation Object Model (FOM) problem arises. She usually has to modify the federate code and rebuilt it. There have been some attempts to solve this problem and they, in fact, accomplish this to some extent but usually they fall short of providing flexible but also a complete mapping me
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Andersson, Peter. "Model based object finding in occluded cluttered environments." Thesis, Umeå University, Department of Computing Science, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-36524.

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<p>The aim of the thesis is object finding in occluded and cluttered environment using computer vision techniques and robot motion. Difficulties of the object finding are 1. finding objects at hidden area and 2. finding unrecognized objects. For solving the difficulties, two methods were developed, one is for finding objects in occluded cluttered environments using model based object finding and the other to increase the robustness in object finding by identifying known objects that are unidentified. The goal was to search occluded areas with the bumblebee2 stereo camera to be able to identify
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Watanabe, Toyohide, Yuuji Yoshida, and Teruo Fukumura. "Editing model based on the object-oriented approach." IEEE, 1988. http://hdl.handle.net/2237/6930.

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Beis, Jeffrey S. "Indexing without invariants in model-based object recognition." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq25014.pdf.

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黃業新 and Yip-san Wong. "A two-level model-based object recognition technique." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31213807.

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Wong, Yip-san. "A two-level model-based object recognition technique /." Hong Kong : University of Hong Kong, 1995. http://sunzi.lib.hku.hk/hkuto/record.jsp?B14705552.

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Rivas, Diaz Juan Manuel. "Model-based object tracking with an infrared stereo camera." Thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-45442.

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Object tracking has become really important in the field of robotics in the last years. Frequently, the goal is to obtain the trajectory of the tracked target over time and space by acquiring and processing information from the sensors. In this thesis we are interested in tracking objects at a very short range. The primary application of our approach is targeting the domain of object tracking during grasp execution with a hand-in-eye sensor setup. To this end, a promising approach investigated in this work is based on the Leap Motion sensor, which is designed for tracking human hands. However,
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Procter, Stephen. "Model-based polyhedral object recognition using edge-triple features." Thesis, University of Surrey, 1998. http://epubs.surrey.ac.uk/843142/.

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While significant progress has been made in the computer vision field over the past decade, and machines capable of performing specialised visual inspection tasks are now being used in many industrial applications, the problem of recognising three-dimensional objects from two-dimensional imagery remains an area of ongoing research. Vision is undoubtedly our most important sense, and solutions to the problem of general three-dimensional machine vision must be found if the long term goal of autonomous robotic agents interacting naturally with humans in the real world is to be realised. In this w
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Yeung, Stephen Siu Kau. "Model-based tactile object recognition using pseudo-random encoding." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/nq21021.pdf.

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Guo, Jing-Ming, Nguyen Van Thinh, and Hua Lee. "Moving Object Detection Based on Ordered Dithering Codebook Model." International Foundation for Telemetering, 2014. http://hdl.handle.net/10150/577451.

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ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA<br>This paper presents an effective multi-layer background modeling method to detect moving objects by exploiting the advantage of novel distinctive features and hierarchical structure of the Codebook (CB) model. In the block-based structure, the mean-color feature within a block often does not contain sufficient texture information, causing incorrect classification especially in large block s
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Books on the topic "Object-Based model"

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Dawson, K. M. Model-based 3-D object recognition using scalartransform descriptors. Trinity College, Department of Computer Science, 1991.

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Darawish, Issam. An object-based analysis and model of on-line auctions. National Library of Canada, 1999.

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Pop, Adrian. Integrated model-driven development environments for equation-based object-oriented languages. Department of Computer and Information Science, Linko pings universitet, 2008.

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Li, Chen-Kuo. AN/SLQ-32 EW system model: An expandable, object-oriented, process-based simulation. Naval Postgraduate School, 1992.

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Adeli, Hojjat. Construction scheduling, cost optimization, and management: A new model based on neurocomputing and object technologies. Spon Press, 2001.

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Han, Yanbo. Software infrastructure for configurable workflow systems: A model-driven approach based on higher order object nets and CORBA. Wissenschaft und Technik, 1997.

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1935-, Lasker G. E., International Institute for Advanced Studies in Systems Research and Cybernetics., and International Conference on Systems Research, Informatics and Cybernetics (9th : 1997 : Baden-Baden, Germany), eds. Advances in database and expert systems: Design issues, data mining, object-oriented databases, generic model for knowledge bases, rapid database prototyping, knowledge-based tools in decision support systems. International Institute for Advanced Studies in Systems Research and Cybernetics, 1997.

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Liu, Jiongxin. Object Part Localization Using Exemplar-based Models. [publisher not identified], 2017.

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Ciancarini, Paolo, Oscar Nierstrasz, and Akinori Yonezawa, eds. Object-Based Models and Languages for Concurrent Systems. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-59450-7.

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Rasch, Jochen. On value based identification in object oriented data models. Inst. für Informatik und Praktische Mathematik, 1998.

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Book chapters on the topic "Object-Based model"

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Sun, Min, and Silvio Savarese. "Model-Based Object Recognition." In Computer Vision. Springer US, 2014. http://dx.doi.org/10.1007/978-0-387-31439-6_334.

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Zhou, Chunbo, and Atsumi Imamiya. "Object-based Linear Undo model." In Human-Computer Interaction INTERACT ’97. Springer US, 1997. http://dx.doi.org/10.1007/978-0-387-35175-9_43.

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Li, Zhongmin, and Zhanwu Yu. "Object-Based Storage Model for Object-Oriented Database." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74784-0_36.

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Ma, Lili, Jian Cheng, Jing Liu, Jinqiao Wang, and Hanqing Lu. "Visual Attention Model Based Object Tracking." In Advances in Multimedia Information Processing - PCM 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15696-0_45.

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Huang, Xiaolei, Zhen Qian, Rui Huang, and Dimitris Metaxas. "Deformable-Model Based Textured Object Segmentation." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11585978_9.

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Sun, Min, and Silvio Savarese. "Model-Based Object Recognition: Traditional Approach." In Computer Vision. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-03243-2_334-1.

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Lienhardt, Michaël, Mario Bravetti, and Davide Sangiorgi. "An Object Group-Based Component Model." In Leveraging Applications of Formal Methods, Verification and Validation. Technologies for Mastering Change. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34026-0_6.

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Sun, Min, and Silvio Savarese. "Model-Based Object Recognition: Traditional Approach." In Computer Vision. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63416-2_334.

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Süß, Jörn Guy, Tim McComb, Soon-Kyeong Kim, Luke Wildman, and Geoffrey Watson. "MDA-Based Re-engineering with Object-Z." In Model Driven Engineering Languages and Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11880240_21.

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Rumpe, Bernhard. "Model-Based Testing of Object-Oriented Systems." In Formal Methods for Components and Objects. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39656-7_16.

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Conference papers on the topic "Object-Based model"

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Danesh, Parisa, Ehsan Amini, and Huseyin Kusetogullari. "Efficient CNN-based Object ID Association Model for Multiple Object Tracking." In 2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). IEEE, 2024. https://doi.org/10.1109/iceccme62383.2024.10796883.

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Mishra, Utkarsh A., and Yongxin Chen. "ReorientDiff: Diffusion Model based Reorientation for Object Manipulation." In 2024 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10610749.

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Klare, Heiko, Timur Saglam, Erik Burger, and Ralf Reussner. "Applying Metamodel-based Tooling to Object-oriented Code." In 7th International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007246202170228.

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Klare, Heiko, Timur Saglam, Erik Burger, and Ralf Reussner. "Applying Metamodel-based Tooling to Object-oriented Code." In 7th International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007246202190230.

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Muller, A., M. Manz, M. Himmelsbach, and H. J. Wunsche. "A model-based object following system." In 2009 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2009. http://dx.doi.org/10.1109/ivs.2009.5164285.

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PHAM, TRONG TON, AUGUSTIN LUX, and THI THANH HAI TRAN. "GRAPH-BASED MODEL FOR OBJECT RECOGNITION." In Proceedings of the First International Conference on Theories and Applications of Computer Science 2006. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772671_0006.

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Shimizu, Atsushi, and Shih-Fu Chang. "Image-object extraction using a genetic-programming-based object model." In Electronic Imaging, edited by Bhaskaran Vasudev, T. Russell Hsing, Andrew G. Tescher, and Robert L. Stevenson. SPIE, 2000. http://dx.doi.org/10.1117/12.382978.

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De-Kai Huang, Kwang-Yu Chen, and Shyi-Chyi Cheng. "Video object detection by model-based tracking." In 2013 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2013. http://dx.doi.org/10.1109/iscas.2013.6572358.

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Geng, Wenjing, Shuzhen Li, Tongwei Ren, and Gangshan Wu. "Object proposals using SVM-based integrated model." In 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, 2016. http://dx.doi.org/10.1109/ijcnn.2016.7727741.

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Thornham, A., C. J. Taylor, and D. Cooper. "Object Cues for Model-based Image Interpretation." In Alvey Vision Conference 1988. Alvey Vision Club, 1988. http://dx.doi.org/10.5244/c.2.9.

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Reports on the topic "Object-Based model"

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Cyganski, David, R. F. Vaz, and J. A. Orr. Model-Based 3-D Object Identification. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada344653.

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Chang, Huey, Katsushi Ikeuchi, and Takeo Kanade. Model-Based Vision System by Object-Oriented Programming. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada195819.

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Michaelis, Stephen. A Model of Suicidal Behavior In Latency Age Children Based on Developmental Object Relations Theory. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.2934.

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Yaroshchuk, Svitlana O., Nonna N. Shapovalova, Andrii M. Striuk, Olena H. Rybalchenko, Iryna O. Dotsenko, and Svitlana V. Bilashenko. Credit scoring model for microfinance organizations. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3683.

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The purpose of the work is the development and application of models for scoring assessment of microfinance institution borrowers. This model allows to increase the efficiency of work in the field of credit. The object of research is lending. The subject of the study is a direct scoring model for improving the quality of lending using machine learning methods. The objective of the study: to determine the criteria for choosing a solvent borrower, to develop a model for an early assessment, to create software based on neural networks to determine the probability of a loan default risk. Used rese
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Heckel, Jeffery S. Building Composer: The Development of an Object Model for Facility Planning and Design Based on Customer Criteria. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada409160.

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Zhang, Caiyun, David Brodylo, Mizanur Rahman, Md Atiqur Rahman, Thomas Douglas, and Xavier Comas. Using an object-based machine learning ensemble approach to upscale evapotranspiration measured from eddy covariance towers in a subtropical wetland. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48056.

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Accurate prediction of evapotranspiration (ET) in wetlands is critical for understanding the coupling effects of water, carbon, and energy cycles in terrestrial ecosystems. Multiple years of eddy covariance (EC) tower ET measurements at five representative wetland ecosystems in the subtropical Big Cypress National Preserve (BCNP), Florida (USA) provide a unique opportunity to assess the performance of the Moderate Resolution Imaging Spectroradiometer (MODIS) ET operational product MOD16A2 and upscale tower measured ET to generate local/regional wetland ET maps. We developed an object-based mac
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Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010891.

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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform l
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Tkachuk, Viktoriia V., Vadym P. Shchokin, and Vitaliy V. Tron. The Model of Use of Mobile Information and Communication Technologies in Learning Computer Sciences to Future Professionals in Engineering Pedagogy. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2668.

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Research goal: the research is aimed at developing a model of use of mobile ICT in learning Computer Sciences to future professionals in Engineering Pedagogy. Object of research is the model of use of mobile ICT in learning Computer Sciences to future professionals in Engineering Pedagogy. Results of the research: the developed model of use of mobile ICT as tools of learning Computer Sciences to future professionals in Engineering Pedagogy is based on the competency-based, person-centered and systemic approaches considering principles of vocational education, general didactic principles, princ
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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-c
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Shyshkina, Mariya P. The Problems of Personnel Training for STEM Education in the Modern Innovative Learning and Research Environment. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2664.

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The aim of the article is to describe the problems of personnel training that arise in view of extension of the STEM approach to education, development of innovative technologies, in particular, virtualization, augmented reality, the use of ICT outsourcing in educational systems design. The object of research is the process of formation and development of the educational and scientific environment of educational institution. The subject of the study is the formation and development of the cloud-based learning and research environment for STEM education. The methods of research are: the analysi
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