Academic literature on the topic 'Hidden objects'

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Journal articles on the topic "Hidden objects"

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Fahle, Manfred. "Detecting hidden objects." Nature 444, no. 7119 (November 2006): 549–50. http://dx.doi.org/10.1038/444549b.

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Zhang, Qing, Gelin Yin, Yongwei Nie, and Wei-Shi Zheng. "Deep Camouflage Images." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (April 3, 2020): 12845–52. http://dx.doi.org/10.1609/aaai.v34i07.6981.

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This paper addresses the problem of creating camouflage images. Such images typically contain one or more hidden objects embedded into a background image, so that viewers are required to consciously focus to discover them. Previous methods basically rely on hand-crafted features and texture synthesis to create camouflage images. However, due to lack of reliable understanding of what essentially makes an object recognizable, they typically result in either complete standout or complete invisible hidden objects. Moreover, they may fail to produce seamless and natural images because of the sensitivity to appearance differences. To overcome these limitations, we present a novel neural style transfer approach that adopts the visual perception mechanism to create camouflage images, which allows us to hide objects more effectively while producing natural-looking results. In particular, we design an attention-aware camouflage loss to adaptively mask out information that make the hidden objects visually standout, and also leave subtle yet enough feature clues for viewers to perceive the hidden objects. To remove the appearance discontinuities between the hidden objects and the background, we formulate a naturalness regularization to constrain the hidden objects to maintain the manifold structure of the covered background. Extensive experiments show the advantages of our approach over existing camouflage methods and state-of-the-art neural style transfer algorithms.
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Guo, Bin, Satoru Satake, and Michita Imai. "Home-Explorer: Ontology-Based Physical Artifact Search and Hidden Object Detection System." Mobile Information Systems 4, no. 2 (2008): 81–103. http://dx.doi.org/10.1155/2008/463787.

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A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects) in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certain conditions, smart objects become hidden ones. However, current systems provide no mechanism to detect and manage objects when this problem occurs. Second, there is no common context infrastructure for building smart artifact systems, which makes it difficult for separately developed applications to interact with each other and uneasy for them to share and reuse knowledge. Unlike previous systems, Home-Explorer builds on an ontology-based knowledge infrastructure named Sixth-Sense, which makes it easy for the system to interact with other applications or agents also based on this ontology. The hidden object problem is also reflected in our ontology, which enables Home-Explorer to deal with both smart objects and hidden objects. A set of rules for deducing an object's status or location information and for locating hidden objects are described and evaluated.
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Haddad, Jeffrey M., Yuping Chen, and Rachel Keen. "Preschoolers search for hidden objects." Journal of Experimental Child Psychology 109, no. 1 (May 2011): 123–31. http://dx.doi.org/10.1016/j.jecp.2010.12.004.

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Drozdek, Adam. "Object-Oriented Programming and Representation of Objects." Studies in Logic, Grammar and Rhetoric 40, no. 1 (March 1, 2015): 293–302. http://dx.doi.org/10.1515/slgr-2015-0014.

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Abstract In this paper, a lesson is drawn from the way class definitions are provided in object-oriented programming. The distinction is introduced between the visible structure given in a class definition and the hidden structure, and then possible connections are indicated between these two structures and the structure of an entity modeled by the class definition.
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Nawroth, C., M. Ebersbach, and E. von Borell. "A note on pigs’ knowledge of hidden objects." Archives Animal Breeding 56, no. 1 (October 10, 2013): 861–72. http://dx.doi.org/10.7482/0003-9438-56-086.

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Abstract. Object permanence is the notion that objects continue to exist even when they are out of observer´s sight. This ability is adaptive not only for free ranging animals who have to cope with a dangerous and highly changeable environment, allowing them to be aware of predators sneaking in their proximity or to keep track of conspecifics or food sources, even when out of sight. Farm animals, too, might profit from object permanence as the ability to follow the trajectory of hidden food or objects may lead to a higher predictability of subjects' environment, which in turn might affect the level of stress under husbandry conditions. We conducted two experiments to examine the ability of object permanence in young domestic pigs (Sus scrofa domestica). For this purpose we used a test setup that was formerly developed for primates and adopted it to the behavioural constraints of pigs. A rewarded object was hidden in one of three hiding locations with an increasing complexity of the objects movement through successive test sessions. Subjects were confronted with visible and invisible displacement tasks as well as with transpositions of hidden objects in different contextual settings. Pigs solved visible, but not invisible displacements or transpositions, indicating that they have difficulties to keep track of once hidden and then moved objects. This should be taken into account when designing husbandry environments or study designs.
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Kibbe, Melissa M., and Alan M. Leslie. "Conceptually Rich, Perceptually Sparse: Object Representations in 6-Month-Old Infants’ Working Memory." Psychological Science 30, no. 3 (January 22, 2019): 362–75. http://dx.doi.org/10.1177/0956797618817754.

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Six-month-old infants can store representations of multiple objects in working memory but do not always remember the objects’ features (e.g., shape). Here, we asked whether infants’ object representations (a) may contain conceptual content and (b) may contain this content even if perceptual features are forgotten. We hid two conceptually distinct objects (a humanlike doll and a nonhuman ball) one at a time in two separate locations and then tested infants’ memory for the first-hidden object by revealing either the original hidden object or an unexpected other object. Using looking time, we found that infants remembered the categorical identity of the hidden object but failed to remember its perceptual identity. Our results suggest that young infants may encode conceptual category in a representation of an occluded object, even when perceptual features are lost.
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Yan, Hui, Zhiguo Gong, Nan Zhang, Tao Huang, Hua Zhong, and Jun Wei. "Crawling Hidden Objects with kNN Queries." IEEE Transactions on Knowledge and Data Engineering 28, no. 4 (April 1, 2016): 912–24. http://dx.doi.org/10.1109/tkde.2015.2502947.

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Lidbetter, Thomas. "Search Games with Multiple Hidden Objects." SIAM Journal on Control and Optimization 51, no. 4 (January 2013): 3056–74. http://dx.doi.org/10.1137/120893938.

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Appleby, Roger, and Colin Cameron. "Seeing hidden objects with millimetre waves." Physics World 25, no. 01 (January 2012): 35–39. http://dx.doi.org/10.1088/2058-7058/25/01/34.

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Dissertations / Theses on the topic "Hidden objects"

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Reid, Sheri Lynn. "Search for hidden objects by pigeons: Place learning vs "object permanence"." Thesis, University of Ottawa (Canada), 1996. http://hdl.handle.net/10393/9707.

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Mental representation of hidden objects by pigeons was tested for. Experiment 1 used a series of Piagetian tests of "object permanence" to measure pigeons' capacity to find a stationary food target behind a screen. Performance on these tests did not differ significantly from chance in spite of manipulations designed to enhance the motivational value of the hidden object. Experiment 2 used operant contingencies to test whether pigeons could mentally represent a moving dot on a computer monitor that temporarily "disappeared" behind a screen. Two target durations were used (12 and 24 seconds) for the dot to move across a computer screen. Pigeons were reinforced if their first keypeck occurred when the dot was hidden but not if it occurred when the dot was visible. Phase 1 consisted of target-12 trials, phase 2 consisted of target-24 trials, and phase 3 consisted of alternating sessions of target-12 and target-24 trials. Results demonstrate that while pigeons were able to use timing strategies to respond correctly with an unconstrained choice method, evidence for the use of mental representations by pigeons was inconclusive. Both experiments are discussed in terms of the mechanisms used by pigeons to find hidden objects.
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Parkinson, Adam Douglas. "Encountering the hidden worlds of musical objects." Thesis, University of Newcastle upon Tyne, 2012. http://hdl.handle.net/10443/3407.

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This thesis articulates an approach to our musical interactions with sounds and technologies influenced by Object Oriented Philosophy and the thought of Gilles Deleuze. The research question is borne out of the practice itself and the questions it poses: how to make sense of my own relationship with sounds as a listener, improviser and composer, and how to understand my engagement with the technologies which mediate this relationship. The most prominent technology I encounter is the laptop, which throughout my practice is used as a musical instrument, and a large part of my research also involves the development of a sensor instrument which utilises the Apple iPhone. The research thus serves as an exploration of both the laptop-as-instrument and certain ‘post laptop’ possibilities, alongside the development of a framework within which to critically consider our relationships to these new instruments. Music involves multiple ‘objects’, a concept which includes (but is not limited to) sounds, songs, instruments, speakers, performers and listeners. Object Oriented Philosophy tells us that these objects are withdrawn: they possess ‘hidden worlds’ or reservoirs of potential that we do not exhaust through any one encounter. Sounds and instruments can be always be used in different ways and reveal different qualities through the networks they are placed in. Listening and playing are construed as being a challenge to find the hidden potentials and affordances in sounds, through changing the way we listen or recontextualising or reworking the sound itself: a range of different strategies for approaching sounds is discussed. I also bring this approach to new instruments - such as laptops, sensor instruments or electronics set-ups - asking what their unique affordances and ‘hidden worlds’ are, and how they might not be actualised should we approach them with fixed ideas about what instruments, performance and music are.
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Ma, Feng. "Discovery of hidden blazars inside quasars /." Digital version accessible at:, 2000. http://wwwlib.umi.com/cr/utexas/main.

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Gariepy, Genevieve. "Imaging light in motion and its application to tracking hidden objects." Thesis, Heriot-Watt University, 2016. http://hdl.handle.net/10399/3371.

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It is well known that light, the fastest entity in the universe, moves at a staggering speed of 300 million meters per second. The ability to stop its flight on a centimetre scale or lower requires a detector with temporal resolution of around a hundred picoseconds. Freezing light in motion at this scale is a feat worth achieving, as it leads to a variety of exciting applications, from observing dynamical light phenomena to measuring distances and depths with high precision, as in LIDAR technology. In the past decades, different technologies have been developed to image light in motion; in this thesis, we propose a new method that exploit a recently-developed single-photon detector technology to capture movies of light in motion at very low intensity levels. We use this method to develop novel imaging applications and detection techniques. In particular, this thesis reports on the observation and study of dynamical light phenomena such as laser propagation in air, laser-induced plasma, propagation in optical fibres and slow light. We also show how the ability to record light in motion can be used to capture light signals scattered from around an obstacle, leading to the ability to locate and track moving objects hidden from view.
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Barth, Jochen. "Search and exploration of hidden objects by great apes and young children." [Maastricht : Maastricht : Universiteit Maastricht] ; University Library, Maastricht University [Host], 2005. http://arno.unimaas.nl/show.cgi?fid=6376.

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Pandharkar, Rohit (Rohit Prakash). "Hidden object doppler : estimating motion, size and material properties of moving non-line-of-sight objects in cluttered environments." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/67783.

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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 111-117).
The thesis presents a framework for Non-Line-of-Sight Computer Vision techniques using wave fronts. Using short-pulse illumination and a high speed time-of-flight camera, we propose algorithms that use multi path light transport analysis to explore the environments beyond line of sight. What is moving around the corner interests everyone including a driver taking a turn, a surgeon performing laparoscopy and a soldier entering enemy base. State of the art techniques that do range imaging are limited by (i) inability to handle multiple diffused bounces [LIDAR] (ii) Wavelength dependent resolution limits [RADAR] and (iii) inability to map real life objects [Diffused Optical Tomography]. This work presents a framework for (a) Imaging the changing Space-time-impulse-responses of moving objects to pulsed illumination (b) Tracking motion along with absolute positions of these hidden objects and (c) recognizing their default properties like material and size and reflectance. We capture gated space-time impulse responses of the scene and their time differentials allow us to gauge absolute positions of moving objects with knowledge of only relative times of arrival (as absolute times are hard to synchronize at femto second intervals). Since we record responses at very short time intervals we collect multiple readings from different points of illumination and thus capturing multi-perspective responses allowing us to estimate reflectance properties. Using this, we categorize and give parametric models of the materials around corner. We hope this work inspires further exploration of NLOS computer vision techniques.
by Rohit Pandharkar.
S.M.
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Maghrabi, Saud M. A. "Algorithms for the removal of hidden edges from computer representations of solid objects." Thesis, University of Hull, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314689.

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Liau, Teh-Fu. "Digital signal processing for the detection of hidden objects using an FMCW radar." Thesis, Queen Mary, University of London, 1987. http://qmro.qmul.ac.uk/xmlui/handle/123456789/1591.

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This thesis deals with the detection of hidden objects using a short-range frequency-modulated continuous wave (FMCW) radar. The detection is carried out by examining the estimated Power Spectral Density (PSD) functions of sampled returns, the peaks of which theoretically correspond to the reflecting surfaces of hidden objects. Fourier and non-Fourier PSD estimation algorithms are applied to the radar returns to extract information on the hidden surfaces. The Fourier methods used are Direct, Blackman-Tukey, Bartlett, and Smoothed Periodograms. The different PSDs are compared, and the validity of each PSD is then discussed. The study is new for this type of radar and the results are used as references for other PSD estimations. Non-Fourier methods offer many advantages. Firstly the Autoregressive Process (AR) is used for this particular application. As well as PSDs the noise spectra are also produced to show the performance of the chosen models. An alternative approach to the conventional forward-backward residuals ( e. g. Burg's method) or autocorrelation and covariance methods ( as those used in speech analysis ) is introduced in this thesis. The stability and good resolution of the PSDs is obtained by a better estimation of the autocovariance coefficients (ACF) from the data available : averaging two p-shifted ACF calculated by covariance method. Once the covariance coefficients are found, the Levinson-Durbin recursive algorithm is used to get the model parameters and the PSDs. Two other non-conventional methods are also attempted to show the image of hidden objects. They are Pisarenko Harmonic Decomposition method and Prony energy spectrum density estimation. In addition to the one-dimensional processing stated above, this thesis extends it to two-dimensional cases, which give more information on the shape of hidden objects.
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Mareschal, Denis. "Visual tracking and the development of object permanence : a connectionist enquiry." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.389084.

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Smith, Simon Paul. "Towards a knowledge management methodology for articulating the role of hidden knowledges." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:32449230-a86a-453b-b9d4-dca2d0b7be3c.

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Knowledge Management Systems are deployed in organisations of all sizes to support the coordination and control of a range of intellectual assets, and the low cost infrastructures made available by the shift to ‘cloud computing’ looks to only increase the speed and pervasiveness of this move. However, their implementation has not been without its problems, and the development of novel interventions capable of supporting the mundane work of everyday organisational settings has ultimately been limited. A common source of trouble for those formulating such systems is said to be that some proportion of the knowledge held by a setting’s members is hidden from the undirected view of both The Organisation and its analysts - typically characterised as a tacit knowledge - and can therefore go unnoticed during the design and deployment of new technologies. Notwithstanding its utility, overuse of this characterisation has resulted in the inappropriate labelling of a disparate assortment of phenomena, some of which might be more appropriately re-specified as ‘hidden knowledges’: a standpoint which seeks to acknowledge their unspoken character without making any unwarranted claims regarding their cognitive status. Approaches which focus on the situated and contingent properties of the actual work carried out by a setting’s members - such as ethnomethodologically informed ethnography - have shown significant promise as a mechanism for transforming the role played by members’ practices into an explicit topic of study. Specifically they have proven particularly adept at noticing those aspects of members’ work that might ordinarily be hidden from an undirected view, such as the methodic procedures through which we can sometimes mean more than we can say in-just-so-many-words. Here - within the context of gathering the requirements for new Knowledge Management Systems to support the reuse of existing knowledge - the findings from the application of just such an approach are presented in the form of a Pattern Language for Knowledge Management Systems: a descriptive device that lends itself to articulating the role that such hidden knowledges are playing in everyday work settings. By combining these three facets, this work shows that it is possible to take a more meaningful approach towards noticing those knowledges which might ordinarily be hidden from view, and apply our new understanding of them to the design of Knowledge Management Systems that actively engage with the knowledgeable work of a setting’s members.
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Books on the topic "Hidden objects"

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Binder, Pat. Seen on Halloween: With hidden objects to count. Norwalk, CT: Innovative Kids, 2000.

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Zwebner, Janet. Uh! oh! Passover Haggadah: With hidden objects you'll (almost) never find. [St. Helier, Jersey?]: Yellow Brick Road, 1994.

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Foundation, Kaplan-Kushlick, South African Jewish Museum, and Isaac Kaplan Collection, eds. Hidden treasures of Japanese art: The Isaac Kaplan Collection. 2nd ed. [Cape Town, South Africa]: Kaplan Kushlick Foundation, 2005.

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guan, Shanghai bo wu, ed. Gu ta yi zhen: Hidden relics from pagodas. Shanghai Shi: Shanghai shu hua chu ban she, 2014.

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Fritz, Armbruster, Baum Hans-Peter, Scherg Leonhard, and Hidden Legacy Foundation, eds. Genizah: Hidden legacies of the German village Jews. Wien: Bertelsmann, 1992.

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Only in Munich: A guide to unique locations, hidden corners and unusual objects. 2nd ed. [England?]: The Urban Explorer, 2014.

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Only in Vienna: A guide to hidden corners, little-known places and unusual objects. Wien: Brandstätter, 2005.

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Asian Art Museum--Chong-Moon Lee Center for Asian Art and Culture, ed. Hidden meanings in Chinese art =: Zhongguo ji xiang tu an. San Francisco: Asian Art Museum of San Francisco, 2006.

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The signs of our time: Semiotics, the hidden messages of environments, objects, and cultural images. Los Angeles: J.P. Tarcher, 1988.

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Obsolete objects in the literary imagination: Ruins, relics, rarities, rubbish, uninhabited places, and hidden treasures. New Haven: Yale University Press, 2006.

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Book chapters on the topic "Hidden objects"

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Ashton, E. H., and J. T. Eayrs. "Detection of Hidden Objects by Dogs." In Ciba Foundation Symposium - Taste and Smell in Vertebrates, 251–63. Chichester, UK: John Wiley & Sons, Ltd., 2008. http://dx.doi.org/10.1002/9780470715369.ch13.

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Kikoin, K., Y. Avishai, and M. N. Kiselev. "Explicit and Hidden Symmetries in Quantum Dots and Quantum Ladders." In Molecular Nanowires and Other Quantum Objects, 177–89. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/978-1-4020-2093-3_17.

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Olszewska, Joanna Isabelle. "Detecting Hidden Objects Using Efficient Spatio-Temporal Knowledge Representation." In Lecture Notes in Computer Science, 302–13. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53354-4_17.

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Yakubov, Vladimir, Sergey Shipilov, Dmitry Sukhanov, and Andrey Klokov. "Radio Tomography of Various Objects Hidden in Clutter Conditions." In Electromagnetic and Acoustic Wave Tomography, 121–65. Boca Raton, FL : CRC Press/Taylor & Francis Group, 2018. | “A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc.”: CRC Press, 2018. http://dx.doi.org/10.1201/9780429488276-6.

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Cîrstea, Corina. "Coalgebra semantics for hidden algebra: Parameterised objects and inheritance." In Recent Trends in Algebraic Development Techniques, 174–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64299-4_33.

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Kuriański, Adam, and Mariusz Nieniewski. "Hidden MRF detection of motion of objects with uniform brightness." In Image Analysis and Processing, 656–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60298-4_328.

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Asghar, Zeeshan, Goshiro Yamamoto, Takafumi Taketomi, Christian Sandor, Hirokazu Kato, and Petri Pulli. "Remote Assistance for Elderly to Find Hidden Objects in a Kitchen." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 3–8. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49655-9_1.

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Yoo, K. M., B. B. Das, F. Liu, Q. Xing, and R. R. Alfano. "Femtosecond Time-Gated Imaging of Translucent Objects Hidden in Highly Scattering Media." In Ultrafast Phenomena VIII, 124–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-84910-7_32.

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Lim, H. L. "Fast Hidden Surface Removal Through Structural Analysis and Representation of Objects and Their Contours." In Computer Graphics 1987, 75–88. Tokyo: Springer Japan, 1987. http://dx.doi.org/10.1007/978-4-431-68057-4_6.

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Keskar, Triveni, Vijay R. Dahake, Kshitij Mittholiya, Archana Hegde, A. M. Basil, and Anuj Bhatnagar. "Development of MATLAB Based Image Stitching Tool for Detection of Hidden Objects at 89 GHz." In Springer Proceedings in Physics, 583–90. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3908-9_73.

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Conference papers on the topic "Hidden objects"

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Turney, J. L., T. N. Mudge, and R. A. Volz. "Recognizing Partially Hidden Objects." In 1984 Cambridge Symposium, edited by David P. Casasent and Ernest L. Hall. SPIE, 1985. http://dx.doi.org/10.1117/12.946169.

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Pao, Y. C., P. Y. Qin, and Q. S. Yuan. "A Fast Sequential Hidden-Line Removal Algorithm." In ASME 1993 International Computers in Engineering Conference and Exposition. American Society of Mechanical Engineers, 1993. http://dx.doi.org/10.1115/cie1993-0079.

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Abstract A fast hidden-line removal algorithm for single convex or concave object, and multiple objects has been developed. It is applicable to both solid objects constructed with planar faces, and with curved surfaces which are represented by meshes. The invisible lines are removed in phases and the computing time in all phases is minimized. Line edges and plane elements involved in the solid object are sorted in the order of their coordinate values. Bounding rectangular boxes are used to determine the overlaps. In place of the trigonometric functions, a simplified linear function is adopted for reducing the computing time. Illustrative examples are presented to demonstrate the practical applications of the developed algorithm.
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Yan, Hui, Zhiguo Gong, Nan Zhang, Tao Huang, Hua Zhong, and Jun Wei. "Crawling hidden objects with kNN queries." In 2016 IEEE 32nd International Conference on Data Engineering (ICDE). IEEE, 2016. http://dx.doi.org/10.1109/icde.2016.7498412.

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Kuzmenko, I. Yu, T. R. Muksunov, and V. P. Yakubov. "LFM locator for hidden objects tomography." In 2014 24th International Crimean Conference "Microwave & Telecommunication Technology" (CriMiCo). IEEE, 2014. http://dx.doi.org/10.1109/crmico.2014.6959738.

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Dalvi, Nilesh, Ravi Kumar, Ashwin Machanavajjhala, and Vibhor Rastogi. "Sampling hidden objects using nearest-neighbor oracles." In the 17th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2020408.2020606.

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Rozban, Daniel, Avihai Aharon Akram, N. S. Kopeika, A. Abramovich, and Assaf Levanon. "Large distance 3D imaging of hidden objects." In SPIE Defense + Security, edited by David A. Wikner and Arttu R. Luukanen. SPIE, 2014. http://dx.doi.org/10.1117/12.2053330.

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Sato, Makoto, and Shuuichiro Imahara. "Clustering Geospatial Objects via Hidden Markov Random Fields." In 2008 Eighth IEEE International Conference on Data Mining (ICDM). IEEE, 2008. http://dx.doi.org/10.1109/icdm.2008.70.

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Rogozhnikov, G. S., and I. V. Mishina. "Imaging of hidden objects in millimeter wavelength range." In 2016 International Conference Laser Optics (LO). IEEE, 2016. http://dx.doi.org/10.1109/lo.2016.7549829.

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Barnum, Peter, Yaser Sheikh, Ankur Datta, and Takeo Kanade. "Dynamic seethroughs: Synthesizing hidden views of moving objects." In 2009 8th IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 2009. http://dx.doi.org/10.1109/ismar.2009.5336483.

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Bentz, Brian Z., John D. van der Laan, Andrew Glen, Christian A. Pattyn, Brian J. Redman, Andres L. Sanchez, Karl R. Westlake, Ryan L. Hastings, Kevin J. Webb, and Jeremy B. Wright. "Detection and localization of objects hidden in fog." In Virtual, Augmented, and Mixed Reality (XR) Technology for Multi-Domain Operations II, edited by Mark S. Dennison, David M. Krum, John (Jack) N. Sanders-Reed, and Jarvis (Trey) J. Arthur. SPIE, 2021. http://dx.doi.org/10.1117/12.2587995.

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