Relevant bibliographies by topics / Time of flight imaging

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

Academic literature on the topic 'Time of flight imaging'

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

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Journal articles on the topic "Time of flight imaging"

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Heide, Felix, Wolfgang Heidrich, Matthias Hullin, and Gordon Wetzstein. "Doppler time-of-flight imaging." ACM Transactions on Graphics 34, no. 4 (2015): 1–11. http://dx.doi.org/10.1145/2766953.

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Achar, Supreeth, Joseph R. Bartels, William L. 'Red' Whittaker, Kiriakos N. Kutulakos, and Srinivasa G. Narasimhan. "Epipolar time-of-flight imaging." ACM Transactions on Graphics 36, no. 4 (2017): 1–8. http://dx.doi.org/10.1145/3072959.3073686.

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Maes, Wouter H. "Practical Guidelines for Performing UAV Mapping Flights with Snapshot Sensors." Remote Sensing 17, no. 4 (2025): 606. https://doi.org/10.3390/rs17040606.

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Uncrewed aerial vehicles (UAVs) have transformed remote sensing, offering unparalleled flexibility and spatial resolution across diverse applications. Many of these applications rely on mapping flights using snapshot imaging sensors for creating 3D models of the area or for generating orthomosaics from RGB, multispectral, hyperspectral, or thermal cameras. Based on a literature review, this paper provides comprehensive guidelines and best practices for executing such mapping flights. It addresses critical aspects of flight preparation and flight execution. Key considerations in flight preparat
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Kim, Juhyeon, Wojciech Jarosz, Ioannis Gkioulekas, and Adithya Pediredla. "Doppler Time-of-Flight Rendering." ACM Transactions on Graphics 42, no. 6 (2023): 1–18. http://dx.doi.org/10.1145/3618335.

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We introduce Doppler time-of-flight (D-ToF) rendering, an extension of ToF rendering for dynamic scenes, with applications in simulating D-ToF cameras. D-ToF cameras use high-frequency modulation of illumination and exposure, and measure the Doppler frequency shift to compute the radial velocity of dynamic objects. The time-varying scene geometry and high-frequency modulation functions used in such cameras make it challenging to accurately and efficiently simulate their measurements with existing ToF rendering algorithms. We overcome these challenges in a twofold manner: To achieve accuracy, w
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Hebden, Jeremy C., and Robert A. Kruger. "Transillumination imaging performance: A time-of-flight imaging system." Medical Physics 17, no. 3 (1990): 351–56. http://dx.doi.org/10.1118/1.596514.

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Giacomantone, Javier, María Lucía Violini, and Luciano Lorenti. "Background Subtraction for Time of Flight Imaging." Journal of Computer Science and Technology 17, no. 02 (2017): e18. http://dx.doi.org/10.24215/16666038.17.e18.

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A time of flight camera provides two types of images simultaneously, depth and intensity. In this paper a computational method for background subtraction, combining both images or fast sequences of images, is proposed. The background model is based on unbalanced or semi-supervised classifiers, in particular support vector machines. A brief review of one class support vector machines is first given. A method that combines the range and intensity data in two operational modes is then provided. Finally, experimental results are presented and discussed.
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Surti, S. "Update on Time-of-Flight PET Imaging." Journal of Nuclear Medicine 56, no. 1 (2014): 98–105. http://dx.doi.org/10.2967/jnumed.114.145029.

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Halimeh, Jad C., and Martin Wegener. "Time-of-flight imaging of invisibility cloaks." Optics Express 20, no. 1 (2011): 63. http://dx.doi.org/10.1364/oe.20.000063.

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Hahne, Uwe, and Marc Alexa. "Exposure Fusion for Time-Of-Flight Imaging." Computer Graphics Forum 30, no. 7 (2011): 1887–94. http://dx.doi.org/10.1111/j.1467-8659.2011.02041.x.

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Kadambi, Achuta, Hang Zhao, Boxin Shi, and Ramesh Raskar. "Occluded Imaging with Time-of-Flight Sensors." ACM Transactions on Graphics 35, no. 2 (2016): 1–12. http://dx.doi.org/10.1145/2836164.

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Dissertations / Theses on the topic "Time of flight imaging"

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Mei, Jonathan (Jonathan B. ). "Algorithms for 3D time-of-flight imaging." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85609.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 57-58).<br>This thesis describes the design and implementation of two novel frameworks and processing schemes for 3D imaging based on time-of- flight (TOF) principles. The first is a low power, low hardware complexity techni
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Petcher, P. A. "Time of flight diffraction and imaging (TOFDI)." Thesis, University of Warwick, 2011. http://wrap.warwick.ac.uk/49478/.

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Time of flight diffraction and imaging (TOFDI) is based on time of flight diffraction (TOFD), adding cross-sectional imaging of the sample bulk by exploiting the scattering of ultrasonic waves from bulk defects in metals. Multiple wave modes are emitted by a pulsed laser ultrasound ablative source, and received by a sparse array of receiving electromagnetic acoustic transducers (EMATs), for non-contact (linear) scanning, with mode-conversions whenever waves are scattered. Standard signal processing techniques, such as band-pass filters, reduce noise. A B-scan is formed from multiple data captu
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Lee, Jason W. L. "Novel developments in time-of-flight particle imaging." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:195be057-7ce0-4a15-b639-b08892fde312.

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In the field of physical chemistry, the relatively recently developed technique of velocity-map imaging has allowed chemical dynamics to be explored with a greater depth than could be previously achieved using other methods. Capturing the scattering image associated with the products resulting from fragmentation of a molecule allows the dissociative pathways and energy landscape to be investigated. In the study of particle physics, the neutron has become an irreplaceable spectroscopic tool due to the unique nature of the interaction with certain materials. Neutron spectroscopy is a non-destruc
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Calvert, N. "Time-of-flight Compton scatter imaging for cargo security." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1503664/.

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By measuring the time of flight of scattered x-ray photons, the point of interaction, assuming a single scatter, can be determined, providing a three dimensional image of cargo containers. The present work introduces the technique, and provides experimental and theoretical results to show the feasibility of such a technique. Monte Carlo simulations were performed to investigate the proportion of multiple scatter detected using a proposed experimental setup, and it was found that it accounted for almost 50% of the recorded signal. Monte Carlo simulations of a scintillation detector were provide
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Noraky, James. "Algorithms and systems for low power time-of-flight imaging." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127029.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, May, 2020<br>Cataloged from the official PDF of thesis.<br>Includes bibliographical references (pages 151-158).<br>Depth sensing is useful for many emerging applications that range from augmented reality to robotic navigation. Time-of-flight (ToF) cameras are appealing depth sensors because they obtain dense depth maps with minimal latency. However, for mobile and embedded devices, ToF cameras, which obtain depth by emitting light and estimating its roundtrip time, can be power-hun
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Yoon, Oh Kyu. "Continuous time-of-flight mass spectrometric imaging of fragmented ions /." May be available electronically:, 2008. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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Westberg, Michael. "Time of Flight Based Teat Detection." Thesis, Linköping University, Department of Electrical Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-19292.

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<p>Time of flight is an imaging technique with uses depth information to capture 3D information in a scene. Recent developments in the technology have made ToF cameras more widely available and practical to work with. The cameras now enable real time 3D imaging and positioning in a compact unit, making the technology suitable for variety of object recognition tasks</p><p>An object recognition system for locating teats is at the center of the DeLaval VMS, which is a fully automated system for milking cows. By implementing ToF technology as part of the visual detection procedure, it would be pos
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Bhandari, Ayush. "Inverse problems in time-of-flight imaging : theory, algorithms and applications." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/95867.

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Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 100-108).<br>Time-of-Fight (ToF) cameras utilize a combination of phase and amplitude information to return real-time, three dimensional information of a scene in form of depth images. Such cameras have a number of scientific and consumer oriented applications. In this work, we formalize a mathematical framework that leads to unifying perspective on tackling inverse problems tha
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Winter, Benjamin. "Novel methods in imaging mass spectrometry and ion time-of-flight detection." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:43db5039-0490-4f97-8519-4d3ed4e30ca3.

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Imaging mass spectrometry (IMS) in microscope mode allows the spatially resolved molecular constitution of a large sample section to be analysed in a single experiment. If performed in a linear mass spectrometer, the applicability of microscope IMS is limited by a number of factors: the low mass resolving power of the employed ion optics; the time resolution afforded by the scintillator screen based particle detector and the multi-hit capability, per pixel, of the employed imaging sensor. To overcome these limitations, this thesis concerns the construction of an advanced ion optic employing a
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Mutamba, Q. B. "Time of flight imaging with 3MeV neutrons based on the associated particle technique." Thesis, Swansea University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.638284.

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Spatial imaging using the time of flight (TOF) method with 3 MeV neutrons based on the associated particle technique has been demonstrated to produce a tomographic image of an aluminium test object. The imaging set-up used coincidence detection of the neutron-induced inelastic scattered gamma rays from the <SUP>27</SUP>Al(n,n'γ)<SUP>27</SUP> Al nuclear reaction in the test object, and the associated <SUP>3</SUP>He particles from the TiD self-implanted target. The test object was positioned 120 cm away from the target, and rotated in the neutron beam at 72 evenly spaced angles of orientation. T
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Books on the topic "Time of flight imaging"

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Anthonys, Gehan. Timing Jitter in Time-of-Flight Range Imaging Cameras. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94159-8.

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Grzegorzek, Marcin, Christian Theobalt, Reinhard Koch, and Andreas Kolb, eds. Time-of-Flight and Depth Imaging. Sensors, Algorithms, and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-44964-2.

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Hansard, Miles. Time-of-Flight Cameras: Principles, Methods and Applications. Springer London, 2013.

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Mutto, Carlo Dal. Time-of-Flight Cameras and Microsoft Kinect™. Springer US, 2012.

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Allāh, Imilī Naṣr. Flight against time. Ragweed Press, 1987.

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Allāh, Imilī Naṣr. Flight against time. Ragweed Press, 1987.

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Allāh, Imilī Naṣr. Flight against time. Center for Middle Eastern Studies, University of Texas at Austin, 1997.

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Hansard, Miles, Seungkyu Lee, Ouk Choi, and Radu Horaud. Time-of-Flight Cameras. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-4658-2.

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Kunstmuseum, Bergen, and Listasfn Reykjavikur, eds. Time: Suspend your flight. Bergen Kunstmuseum, 2000.

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Kight, Pat. The flight of time. printed by Cascade Printing, 1988.

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Book chapters on the topic "Time of flight imaging"

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Gupta, Mohit. "Depth from Time-of-Flight Imaging." In Coded Optical Imaging. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-39062-3_16.

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Broadstone, Steven R., and R. Martin Arthur. "Time-of-Flight Approximation for Medical Ultrasonic Imaging." In Acoustical Imaging. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-0725-9_16.

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Sabatini, Angelo M. "Modeling in-Air Ultrasonic Time-of-Flight Noise." In Acoustical Imaging. Springer US, 1996. http://dx.doi.org/10.1007/978-1-4419-8772-3_103.

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Nieuwenhove, Daniël Van. "Time-of-Flight 3D-Imaging Techniques." In Interactive Displays. John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118706237.ch7.

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Böhme, Martin, Martin Haker, Kolja Riemer, Thomas Martinetz, and Erhardt Barth. "Face Detection Using a Time-of-Flight Camera." In Dynamic 3D Imaging. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03778-8_13.

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Benaron, David A., David C. Ho, Stanley Spilman, John P. Van Houten, and David K. Stevenson. "Tomographic Time-of-Flight Optical Imaging Device." In Advances in Experimental Medicine and Biology. Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-1875-4_26.

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Lindner, Marvin, and Andreas Kolb. "Compensation of Motion Artifacts for Time-of-Flight Cameras." In Dynamic 3D Imaging. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03778-8_2.

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Bleiweiss, Amit, and Michael Werman. "Fusing Time-of-Flight Depth and Color for Real-Time Segmentation and Tracking." In Dynamic 3D Imaging. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03778-8_5.

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Anthonys, Gehan. "ToF Range Imaging Cameras." In Timing Jitter in Time-of-Flight Range Imaging Cameras. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-94159-8_2.

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Kohoutek, Tobias K., David Droeschel, Rainer Mautz, and Sven Behnke. "Indoor Positioning and Navigation Using Time-Of-Flight Cameras." In TOF Range-Imaging Cameras. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-27523-4_8.

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Conference papers on the topic "Time of flight imaging"

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Coldwell, Cooper, Karsten Schnier, Anirban Swakshar, Sevgi Gurbuz, Seongsin M. Kim, and Patrick Kung. "Guided super-resolution of time-of-flight imaging using multimodal deep learning." In Real-Time Image Processing and Deep Learning 2025, edited by Nasser Kehtarnavaz and Mukul V. Shirvaikar. SPIE, 2025. https://doi.org/10.1117/12.3053961.

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Li, Fengqiang, Huaijin Chen, Chia-Kai Yeh, et al. "Compressive Time-of-Flight Imaging." In Applied Industrial Optics: Spectroscopy, Imaging and Metrology. OSA, 2018. http://dx.doi.org/10.1364/aio.2018.am2a.5.

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Heide, Felix, Gordon Wetzstein, Matthias Hullin, and Wolfgang Heidrich. "Doppler time-of-flight imaging." In SIGGRAPH '15: Special Interest Group on Computer Graphics and Interactive Techniques Conference. ACM, 2015. http://dx.doi.org/10.1145/2782782.2792497.

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Antholzer, Stephan, Christoph Wolf, Michael Sandbichler, Markus Dielacher, and Markus Haltmeier. "Compressive time-of-flight imaging." In 2017 International Conference on Sampling Theory and Applications (SampTA). IEEE, 2017. http://dx.doi.org/10.1109/sampta.2017.8024403.

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Li, Fengqiang, Huaijin Chen, Chiakai Yeh, Ashok Veeraraghavan, and Oliver Cossairt. "High spatial resolution time-of-flight imaging." In Computational Imaging III, edited by Amit Ashok, Jonathan C. Petruccelli, Abhijit Mahalanobis, and Lei Tian. SPIE, 2018. http://dx.doi.org/10.1117/12.2303794.

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Schaller, Christian, Andre Adelt, Jochen Penne, and Joachim Hornegger. "Time-of-Flight sensor for patient positioning." In SPIE Medical Imaging, edited by Michael I. Miga and Kenneth H. Wong. SPIE, 2009. http://dx.doi.org/10.1117/12.812498.

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Li, Fengqiang, Florian Willomitzer, Prasanna Rangarajan, Andreas Velten, Mohit Gupta, and Oliver Cossairt. "Micro Resolution Time-of-Flight Imaging." In 3D Image Acquisition and Display: Technology, Perception and Applications. OSA, 2018. http://dx.doi.org/10.1364/3d.2018.3w2g.2.

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Li, Fengqiang, Florian Willomitzer, Prasanna Rangarajan, Andreas Velten, Mohit Gupta, and Oliver Cossairt. "Micro Resolution Time-of-Flight Imaging." In Computational Optical Sensing and Imaging. OSA, 2018. http://dx.doi.org/10.1364/cosi.2018.cm2e.4.

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Charbon, Edoardo. "Introduction to time-of-flight imaging." In 2014 IEEE Sensors. IEEE, 2014. http://dx.doi.org/10.1109/icsens.2014.6985072.

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Velten, Andreas, Moungi Bawendi, and Ramesh Raskar. "Picosecond Camera for Time-of-Flight Imaging." In Imaging Systems and Applications. OSA, 2011. http://dx.doi.org/10.1364/isa.2011.imb4.

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Reports on the topic "Time of flight imaging"

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H. FUNSTEN. IMAGING TIME-OF-FLIGHT ION MASS SPECTROGRAPH. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/768176.

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Desa, Hazry, and Muhammad Azizi Azizan. OPTIMIZING STOCKPILE MANAGEMENT THROUGH DRONE MAPPING FOR VOLUMETRIC CALCULATION. Penerbit Universiti Malaysia Perlis, 2023. http://dx.doi.org/10.58915/techrpt2023.004.

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Stockpile volumetric calculation is an important aspect in many industries, including construction, mining, and agriculture. Accurate calculation of stockpile volumes is essential for efficient inventory management, logistics planning, and quality control. Traditionally, stockpile volumetric calculation is done using ground-based survey methods, which can be time-consuming, labour-intensive, and often inaccurate. However, with the recent advancements in drone technology, it has become possible to use drones for stockpile volumetric calculation, providing a faster, safer, and more accurate solu
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Copley, John R. D. Neutron time-of-flight spectroscopy. National Institute of Standards and Technology, 1998. http://dx.doi.org/10.6028/nist.ir.6205.

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Marleau, Peter, Erik Brubaker, Mark D. Gerling, Patricia Frances Schuster, and John T. Steele. Time Encoded Radiation Imaging. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1113859.

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Rockwell, Donald. Space-Time Imaging Systems. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada584973.

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Dietrick, Robert A. Hypersonic Flight: Time To Go Operational. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ad1018856.

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Zare, Richard N., Matthew D. Robbins, Griffin K. Barbula, and Richard Perry. Hadamard Transform Time-of-Flight Spectroscopy. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada564594.

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Chiang, I.-Hung, Adam Rusek, and M. Sivertz. Time of Flight of NSRL Beams. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/1775544.

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Watson, Thomas B. Proton Transfer Time-of-Flight Mass Spectrometer. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1251396.

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Zare, Richard N., Matthew D. Robbins, Griffin K. Barbula, and Richard Perry. Hadamard Transform Time-of-Flight Mass Spectrometry. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada589689.

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