Relevant bibliographies by topics / Computer generated images

Contents

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

Academic literature on the topic 'Computer generated images'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Computer generated images"

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Kerlow, Isaac Victor. "Computer-generated images and traditional printmaking." Visual Computer 4, no. 1 (1988): 8–18. http://dx.doi.org/10.1007/bf01901075.

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Ramek, Michael. "Colour vision and computer-generated images." Journal of Physics: Conference Series 237 (June 1, 2010): 012018. http://dx.doi.org/10.1088/1742-6596/237/1/012018.

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Bouhali, Othmane, and Ali Sheharyar. "Distributed rendering of computer-generated images on commodity compute clusters." Qatar Foundation Annual Research Forum Proceedings, no. 2012 (October 2012): CSP16. http://dx.doi.org/10.5339/qfarf.2012.csp16.

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Lucas, Gale M., Bennett Rainville, Priya Bhan, Jenna Rosenberg, Kari Proud, and Susan M. Koger. "Memory for Computer-Generated Graphics: Boundary Extension in Photographic vs. Computer-Generated Images." Psi Chi Journal of Psychological Research 10, no. 2 (2005): 43–48. http://dx.doi.org/10.24839/1089-4136.jn10.2.43.

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Sando, Yusuke, Masahide Itoh, and Toyohiko Yatagai. "Color computer-generated holograms from projection images." Optics Express 12, no. 11 (2004): 2487. http://dx.doi.org/10.1364/opex.12.002487.

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Wanger, L. R., J. A. Ferwerda, and D. P. Greenberg. "Perceiving spatial relationships in computer-generated images." IEEE Computer Graphics and Applications 12, no. 3 (1992): 44–58. http://dx.doi.org/10.1109/38.135913.

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Katoh, N., and M. Ito. "Gamut Mapping for Computer Generated Images (II)." Color and Imaging Conference 4, no. 1 (1996): 126–28. http://dx.doi.org/10.2352/cic.1996.4.1.art00034.

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Pini, Ezequiel. "Computer Generated Inspiration." Temes de Disseny, no. 36 (October 1, 2020): 192–207. http://dx.doi.org/10.46467/tdd36.2020.192-207.

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This pictorial addresses the new use of Computer Generated Imagery as a tool for contextualising and inspiring futures. Using research through design experimental methodology, these techniques allow us to create utopic spaces by embracing accidental outcomes, displaying an as yet unexplored path lacking the limitations of the real world. The resulting images prove how 3D digital imagery used in the design context can serve as a new medium for artistic self-expression, as a tool for future designs and as an instrument to raise awareness about environmental challenges. The term we have coined, C
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Subong, Ryan, and AlmaJean Subong. "Computer-Generated Sand Mixtures and Sand-based Images." International Journal of Computing Sciences Research 8 (January 1, 2024): 3119–30. https://doi.org/10.25147/ijcsr.2017.001.1.207.

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Purpose–This paper aims to verify the effectiveness of the software implementation of the proposed algorithm in creating computer-generated images of sand mixtures using a photograph of sand as an input and its effectiveness in converting digital pictures into sand-based images out of the mixtures it generated. Method–Visually compare the photographed image of the actual mixtures to its computer-generated counterpart to verify if the mixture generation produces results as expected and compare the computer-generated sand-based images with its source to verify image reproduction maintains same i
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Wang, Yan, and Xiao Wang. "Preprocessing and Edge Detection of Natural Images and Computer Generated Images." International Journal of Signal Processing, Image Processing and Pattern Recognition 9, no. 5 (2013): 281–90. http://dx.doi.org/10.14257/ijsip.2016.9.5.25.

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Dissertations / Theses on the topic "Computer generated images"

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Evans, Steven R. "The pixel generator : a VLSI device for computer generated images." Thesis, University of Sussex, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.332912.

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Strassmann, Steven Henry. "Hairy brushes in computer-generated images." Thesis, Massachusetts Institute of Technology, 1986. http://hdl.handle.net/1721.1/78948.

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Quan, Weize. "Detection of computer-generated images via deep learning." Thesis, Université Grenoble Alpes, 2020. http://www.theses.fr/2020GRALT076.

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Avec les progrès des outils logiciels d'édition et de génération d'images, il est devenu plus facile de falsifier le contenu des images ou de créer de nouvelles images, même pour les novices. Ces images générées, telles que l'image de rendu photoréaliste et l'image colorisée, ont un réalisme visuel de haute qualité et peuvent potentiellement menacer de nombreuses applications importantes. Par exemple, les services judiciaires doivent vérifier que les images ne sont pas produites par la technologie de rendu infographique, les images colorisées peuvent amener les systèmes de reconnaissance / sur
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Bassanino, May Nahab. "The perception of computer generated architectural images." Thesis, University of Liverpool, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367240.

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Beale, Gareth. "Representing Roman statuary using computer generated images." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/375493/.

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This thesis explores the potential of computer graphics as a means of producing hypothetical visual reconstructions of a painted statue of a young woman discovered at Herculaneum in 2006 (inv. 4433/87021). The visualisations incorporate accurate representation of experimentally derived data using physically accurate rendering techniques. The statue is reconstructed according to a range of different hypotheses and is visualised within a selection of architectural contexts. The work presented here constitutes both a technical and theoretical innovation for archaeological research. The methodolog
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Cartwright, Paul. "Realisation of computer generated integral three dimensional images." Thesis, De Montfort University, 2000. http://hdl.handle.net/2086/13289.

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Payne, Doug. "Simulating perceived 3D images replayed by computer generated holograms." Thesis, Heriot-Watt University, 2004. http://hdl.handle.net/10399/355.

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Rosenzweig, Elizabeth. "A personal color proofing system for computer generated images." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/77304.

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Thesis (M.S.V.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1985.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.<br>Includes bibliographical references (leaves 71-73).<br>Just as the invention of photography challenged the world's visual literacy at the turn of the century, so has computer graphics begun to reshape visual communication. Although still in its infancy, recently developed tools for visual communication have made computer graphics and electronic imaging accessible to a much larger number of artists and other professionals. The use of these systems has emp
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Youssef, Osama Hassan. "Acceleration techniques for photo realistic computer generated integral images." Thesis, De Montfort University, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.699807.

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Oglesby, Corliss Deionn. "The New Frontier of Advertising: Computer-Generated Images as Influencers." UNF Digital Commons, 2019. https://digitalcommons.unf.edu/etd/861.

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The use of computer-generated images as influencers of consumer opinions and behavior is an emerging advertising strategy. This research investigates the advantages and disadvantages of using computer-generated images (CGI) as influencers of human behavior from the perspective of promoting a brand. The power of electronic word of mouth (social media) and how it is incorporated in computer-generated images used as influencers is discussed as a major factor in consumer decision making. The social media account content of computer-generated images was analyzed by conducting a frame analysis to di
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Books on the topic "Computer generated images"

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Magnenat-Thalmann, Nadia, and Daniel Thalmann, eds. Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8.

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Ihaddaden, Youcef. CGI: Computer generated images. Films for the Humanities & Sciences, 2005.

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Bigand, André, Julien Dehos, Christophe Renaud, and Joseph Constantin. Image Quality Assessment of Computer-generated Images. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73543-6.

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Cartwright, Paul. Realisation of computer generated integral three dimensional images. De Montfort University, 2000.

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Smarandache, Florentin. Hieroglyphs & diagrams: Computer-generated outer-art : composed, found, changed, modified, alternated computer-programmed images. F. Smarandache, 2006.

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Magnenat-Thalmann, Nadia. Computer-Generated Images: The State of the Art Proceedings of Graphics Interface '85. Springer Japan, 1985.

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Napleton, Steven. The technological and aesthetic impact of computer-generated images on the Hollywood cinema. University of East London, 2000.

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Huber, Dieter. Klones: Computergenerierte Fotoarbeiten = computer generated photographs. Verlag für Moderne Kunst, 1997.

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Osipenko, Georgiy. Computer-oriented methods of dynamic systems. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1912470.

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The methods of studying the global properties of dynamic systems based on the construction of a symbolic image of this system are considered. A symbolic image is an oriented graph, which is an approximation to a dynamical system and is constructed by discretizing the phase space. The symbolic dynamics generated by the oriented graph reflects the dynamics of the system under study. The symbolic image is a tool of theoretical research and the basis of computer-oriented methods for the numerical study of nonlocal properties of dynamical systems.&#x0D; Meets the requirements of the federal state e
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D, Phillips James, and Ames Research Center, eds. A computational method to model radar return range in a polygonally based, computer-generated-imagery simulation. National Aeronautics and Space Administration, Ames Research Center, 1986.

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Book chapters on the topic "Computer generated images"

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Greenberg, Joel M. "Computer Animation in Distance Teaching." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_22.

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Cléroux, R., Y. Lepage, and N. Ranger. "Computer Graphics for Multivariate Data." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_35.

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Heath, A. M., and R. B. Flavell. "Colour Coding Scales and Computer Graphics." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_27.

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Ratib, Osman, and Alberto Righetti. "Computer Analysis of Cardiac Wall Motion Asynchrony." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_9.

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Zeltzer, David. "Towards an Integrated View of 3-D Computer Animation." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_20.

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Lichten, Larry, and Ronald Eaton. "An Innovative User Interface for Microcomputer-Based Computer-Aided Design." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_28.

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Mills, Michael I. "Image Synthesis." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_1.

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Michaud, C., A. S. Malowany, and M. D. Levine. "Multi-Robot Assembly of IC’s." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_10.

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Appel, R., M. Funk, C. Pellegrini, D. Hochstrasser, and A. F. Müller. "A Computerized System for Spot Detection and Analysis of Two-Dimensional Electrophoresis Images." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_11.

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Prusinkiewicz, Przemyslaw, and Mark Christopher. "Hologram-Like Transmission of Pictures." In Computer-Generated Images. Springer Japan, 1985. http://dx.doi.org/10.1007/978-4-431-68033-8_12.

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Conference papers on the topic "Computer generated images"

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Li, Ji, and Kai Wang. "Detecting computer-generated images by using only real images." In Seventeenth International Conference on Machine Vision (ICMV 2024), edited by Wolfgang Osten. SPIE, 2025. https://doi.org/10.1117/12.3055092.

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Shimobaba, Tomoyoshi, Minsung Kang, Fan Wang, Kai Rumano, and Tomoyoshi Ito. "NeRF-based computer-generated holography." In Digital Holography and Three-Dimensional Imaging. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/dh.2024.m1b.1.

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This study introduces hologram generation from two-dimensional images using neural radiance fields (NeRF). The proposed method enables the generation of holograms capable of reproducing 3D images viewing at arbitrary viewpoints.
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Aditto, Tarvir Anjum, Md Rakib Shahariar, and Hafiz Imtiaz. "A Robust Image Watermarking Approach for Application in AI Generated Images." In 2024 13th International Conference on Electrical and Computer Engineering (ICECE). IEEE, 2024. https://doi.org/10.1109/icece64886.2024.11025115.

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Vahdati, Danial Samadi, Tai D. Nguyen, Aref Azizpour, and Matthew C. Stamm. "Beyond Deepfake Images: Detecting AI-Generated Videos." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2024. http://dx.doi.org/10.1109/cvprw63382.2024.00443.

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Oo, Su Thet, Phyu Phyu Htun, Lai Yee Win Lwin, Ah Nge Htwe, and Nilar Aye. "Classifying Real versus AI Generated Images using CIFAR-10 Network and Painting Image Data." In 2025 IEEE Conference on Computer Applications (ICCA). IEEE, 2025. https://doi.org/10.1109/icca65395.2025.11011094.

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Naidu, Gangu Rama, and Chanamallu Srinivasa Rao. "An Optimized Deep Learning Model For Photographic Images And Photorealistic Computer-Generated Graphics Image Classification." In 2024 IEEE 2nd International Conference on Innovations in High Speed Communication and Signal Processing (IHCSP). IEEE, 2024. https://doi.org/10.1109/ihcsp63227.2024.10960071.

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Dimitri, Giovanna Maria, Benedetta Tondi, and Mauro Barni. "Enhancing Synthetic Generated-Images Detection through Post-Hoc Calibration." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW). IEEE, 2025. https://doi.org/10.1109/wacvw65960.2025.00087.

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Qin, Zhenyue, Yiqun Zhang, Yang Liu, and Dylan Campbell. "HandCraft: Anatomically Correct Restoration of Malformed Hands in Diffusion Generated Images." In 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. https://doi.org/10.1109/wacv61041.2025.00386.

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Kornfeld, Gertrude H. "Interpreting computer-generated IR images." In OSA Annual Meeting. Optica Publishing Group, 1986. http://dx.doi.org/10.1364/oam.1986.thc2.

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Computer generation of infrared imagery for automatic target recognizer (ATR) evaluation and human perception studies is discussed in this presentation. Initially a videotape with driving vehicles and observer motion is shown. A comparison of forward-looking infrared radiometer (FLIR) imagery and computer generations demonstrates achieved realism. A computer-generated FLIR search pattern with an approaching tank demonstrates a motion that is difficult to detect by humans, but ATRs programmed for center of hot spot detection and frames subtraction might detect the tank motion. Finally, a simula
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Hazza, Zubaidah Muataz, and Normaziah Abdul Aziz. "Detecting Computer Generated Images for Image Spam Filtering." In 2012 International Conference on Advanced Computer Science Applications and Technologies (ACSAT). IEEE, 2012. http://dx.doi.org/10.1109/acsat.2012.38.

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Reports on the topic "Computer generated images"

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Johra, Hicham, Martin Veit, Mathias Østergaard Poulsen, et al. Training and testing labelled image and video datasets of human faces for different indoor visual comfort and glare visual discomfort situations. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau542153983.

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The aim of this technical report is to provide a description and access to labelled image and video datasets of human faces that have been generated for different indoor visual comfort and glare visual discomfort situations. These datasets have been used to train and test a computer-vision artificial neural network detecting glare discomfort from images of human faces.
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Mbani, Benson, Timm Schoening, and Jens Greinert. Automated and Integrated Seafloor Classification Workflow (AI-SCW). GEOMAR, 2023. http://dx.doi.org/10.3289/sw_2_2023.

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The Automated and Integrated Seafloor Classification Workflow (AI-SCW) is a semi-automated underwater image processing pipeline that has been customized for use in classifying the seafloor into semantic habitat categories. The current implementation has been tested against a sequence of underwater images collected by the Ocean Floor Observation System (OFOS), in the Clarion-Clipperton Zone of the Pacific Ocean. Despite this, the workflow could also be applied to images acquired by other platforms such as an Autonomous Underwater Vehicle (AUV), or Remotely Operated Vehicle (ROV). The modules in
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Fader, G. B. J., R. O. Miller, and B. J. Todd. Geological interpretation of Halifax Harbour, Nova Scotia, Canada. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331504.

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An important part of seabed mapping is understanding the shape of the seabed and the depth of water. Hydrographic charts are produced for this purpose by the Canadian Hydrographic Service. During the final survey stages of the Harbour a new technology called multibeam bathymetry became available for high resolution mapping. This system uses transducers (sound sources) mounted on a ship that produce many independent sound beams and can map a large swath of the seabed at one time covering 100% of the bottom. The images that are produced are computer shaded to look as if the water is drained and
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Glandon, S. Ross, Casey L. Lorenzen, William F. Farthing, et al. Analysis tools and techniques for evaluating quality in synthetic data generated by the Virtual Autonomous Navigation Environment. US Army Engineer Research and Development Center, 2025. https://doi.org/10.21079/11681/49708.

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The capability to produce high-quality labeled synthetic image data is an important tool for building and maintaining machine learning datasets. However, ensuring computer-generated data is of high quality is very challenging. This report describes an effort to evaluate and improve synthetic image data generated by the Virtual Autonomous Navigation Environment’s Environment and Sensor Engine (VANE::ESE), as well as documenting a set of tools developed to process, analyze, and train models from, image datasets generated by VANE::ESE. Additionally, the results of several experiments are presente
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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7585193.bard.

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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are ob
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Atherosclerosis Biomarkers by Computed Tomography Angiography (CTA). Chair Andrew Buckler, Luca Saba, and Uwe Joseph Schoepf. Radiological Society of North America (RSNA) / Quantitative Imaging Biomarkers Alliance (QIBA), 2023. http://dx.doi.org/10.1148/qiba/20230328.

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The clinical application of Computed Tomography Angiography (CTA) is widely available as a technique to optimize the therapeutic approach to treating vascular disease. Evaluation of atherosclerotic arterial plaque characteristics is currently based on qualitative biomarkers. However, the reproducibility of such findings has historically been limited even among experts (1). Quantitative imaging biomarkers have been shown to have additive value above traditional qualitative imaging metrics and clinical risk scores regarding patient outcomes (2). However, many definitions and cut-offs are present
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Saba, Luca, and Uwe Joseph Schoepf. Atherosclerosis Biomarkers by Computed Tomography Angiography (CTA) - Maintenance version June 2024. Chair Andrew Buckler. Radiological Society of North America (RSNA) / Quantitative Imaging Biomarkers Alliance (QIBA), 2024. http://dx.doi.org/10.1148/qiba/202406.

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The clinical application of Computed Tomography Angiography (CTA) is widely available as a technique to optimize the therapeutic approach to treating vascular disease. Evaluation of atherosclerotic arterial plaque characteristics is currently based on qualitative biomarkers. However, the reproducibility of such findings has historically been limited even among experts. Quantitative imaging biomarkers have been shown to have additive value above traditional qualitative imaging metrics and clinical risk scores regarding patient outcomes. However, many definitions and cut-offs are present in the
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Fader, G. B. J., R. O. Miller, and B. J. Todd. Making a three-dimensional model of Halifax Harbour, Nova Scotia, Canada. Natural Resources Canada/CMSS/Information Management, 2023. http://dx.doi.org/10.4095/331507.

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Halifax Harbour is one of best-studied harbours in the world. Researchers at the Bedford Institute of Oceanography map the seabed, perform geochemical analyses of sediment core samples, measure currents and tides and study the effects of pollution on the biota. To illustrate the complexity and intricate detail that exists on the seabed, a physical relief model of the harbour and surrounding area was constructed using the most recent technology. The model, which was milled from lightweight surfboard foam, shows underwater relief (bathymetry) as well as the land topography. Onshore, high-resolut
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Lasko, Kristofer, Francis O’Neill, and Elena Sava. Automated mapping of land cover type within international heterogenous landscapes using Sentinel-2 imagery with ancillary geospatial data. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49367.

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A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover m
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Malinowski, Owen, Scott Riccardella, and Jason Van Velsor. PR-335-203810-R03 CT Fundamentals with Calibration and Reference Standards for Pipeline Anomaly Detection. Pipeline Research Council International, Inc. (PRCI), 2022. http://dx.doi.org/10.55274/r0012216.

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X-ray Computed Tomography (XRCT) was initially developed and utilized in the medical industry to image the internal structure of the human body. X-ray imaging was conceived and realized at the turn of the 20th century and subsequently, XRCT, was conceived in the middle of the 20th century and its development continues today. Near the end of the 20th century industrial cone beam XRCT for applications such as dimensional metrology branched off, including its use for identifying and dimensioning flaws. XRCT has been utilized successfully for three-dimensional imaging of flaws in the small panel c
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