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Relevant bibliographies by topics / The image of hand

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Academic literature on the topic 'The image of hand'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "The image of hand"

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Hegdé, Jay, Nicholas J. Tustison, William T. Parker, Fallon Branch, Nathan Yanasak, and Lorie A. Stumpo. "An Anatomical Template for the Normalization of Medical Images of Adult Human Hands." Diagnostics 13, no. 12 (2023): 2010. http://dx.doi.org/10.3390/diagnostics13122010.

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During medical image analysis, it is often useful to align (or ‘normalize’) a given image of a given body part to a representative standard (or ‘template’) of that body part. The impact that brain templates have had on the analysis of brain images highlights the importance of templates in general. However, templates for human hands do not exist. Image normalization is especially important for hand images because hands, by design, readily change shape during various tasks. Here we report the construction of an anatomical template for healthy adult human hands. To do this, we used 27 anatomicall

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He, Wangyong, Zhongzhao Xie, Yongbo Li, Xinmei Wang, and Wendi Cai. "Synthesizing Depth Hand Images with GANs and Style Transfer for Hand Pose Estimation." Sensors 19, no. 13 (2019): 2919. http://dx.doi.org/10.3390/s19132919.

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Hand pose estimation is a critical technology of computer vision and human-computer interaction. Deep-learning methods require a considerable amount of tagged data. Accordingly, numerous labeled training data are required. This paper aims to generate depth hand images. Given a ground-truth 3D hand pose, the developed method can generate depth hand images. To be specific, a ground truth can be 3D hand poses with the hand structure contained, while the synthesized image has an identical size to that of the training image and a similar visual appearance to the training set. The developed method,

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Zhang, Haozhuo, Bin Zhu, Yu Cao, and Yanbin Hao. "Hand1000: Generating Realistic Hands from Text with Only 1,000 Images." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 9 (2025): 9905–13. https://doi.org/10.1609/aaai.v39i9.33074.

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Text-to-image generation models have achieved remarkable advancements in recent years, aiming to produce realistic images from textual descriptions. However, these models often struggle with generating anatomically accurate representations of human hands. The resulting images frequently exhibit issues such as incorrect numbers of fingers, unnatural twisting or interlacing of fingers, or blurred and indistinct hands. These issues stem from the inherent complexity of hand structures and the difficulty in aligning textual descriptions with precise visual depictions of hands. To address these chal

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Chyad, Haitham Salman, Raniah Ali Mustafa, and Kawther Thabt Saleh. "Hand Print Recognition System based on FP-Growth Algorithm." Webology 19, no. 1 (2022): 980–1000. http://dx.doi.org/10.14704/web/v19i1/web19067.

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Hand print recognition system received great interest in the recent few years such as human-computer interaction, computer vision, and computer graphics. In this paper, proposed system for recognition human handprint based on FP-growth algorithm, the system consists of three-stage. The first stage the detection algorithm using HSV color space, canny algorithm and contrast enhancement for grayscale. In this stage separate skin area in-handprint image through first HSV color space converting RGB to HSV color space as well as conducting specific rules for determining the skin area. And then appli

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Ju, Shengtai, Amy R. Reibman, and Amanda J. Deering. "Robust hand hygiene monitoring for food safety using hand images." Electronic Imaging 35, no. 7 (2023): 275–1. http://dx.doi.org/10.2352/ei.2023.35.7.image-275.

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Pavani, Francesco, and Massimiliano Zampini. "The Role of Hand Size in the Fake-Hand Illusion Paradigm." Perception 36, no. 10 (2007): 1547–54. http://dx.doi.org/10.1068/p5853.

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When a hand (either real or fake) is stimulated in synchrony with our own hand concealed from view, the felt position of our own hand can be biased toward the location of the seen hand. This intriguing phenomenon relies on the brain's ability to detect statistical correlations in the multisensory inputs (ie visual, tactile, and proprioceptive), but it is also modulated by the pre-existing representation of one's own body. Nonetheless, researchers appear to have accepted the assumption that the size of the seen hand does not matter for this illusion to occur. Here we used a real-time video imag

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Pornpanomchai, Chomtip. "Image-Based Hand Tools and Accessories Recognition by ResNet50." International Journal of Membrane Science and Technology 10, no. 2 (2023): 3620–29. http://dx.doi.org/10.15379/ijmst.v10i2.3193.

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The objective of this research is to create a computer system which can recognize various kinds of hand-tools by using only a single image. The developed system is called “Hand-tool and accessory image recognition system or (HTAIRS)”. The system consists of 4 main modules, namely: 1) dataset training, 2) image acquisition, 3) image recognition, and 4) result presentation modules. The system employs the convolutional neural networks (CNN) called “ResNet50”, which is a toolbox in MATLAB software. The developed system creates its own dataset called “Hand Tools Dataset”, which consists of 165 diff

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Shibuya, Satoshi. "Effects of Orientation and Appearance of a Synchronously Moving Object on Hand Movements." Psych 2, no. 4 (2020): 287–95. http://dx.doi.org/10.3390/psych2040022.

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Various devices have been developed to enable humans to control remote objects using active hand movements. However, it is still unclear how the visual characteristics of a synchronously moving object influences hand movements. This study investigates the effects of visual appearance and orientation of a hand-controlled object on hand movements using a novel visuomotor task. The motion of a visual image on a monitor reflected the participants’ right hand movements in the forwards-backwards direction, but not in the lateral direction (i.e., the lateral position of the image was fixed). Particip

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Tomida, Motomasa, and Kiyoshi Hoshino. "Visual-Servoing Control of Robot Hand with Estimation of Full Articulation of Human Hand." Key Engineering Materials 625 (August 2014): 728–35. http://dx.doi.org/10.4028/www.scientific.net/kem.625.728.

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A depth sensor or depth camera is available at a reasonable cost in recent years. Due to the excessive dispersion of depth values outputted from the depth camera, however, changes in the pose cannot be directly employed for complicated hand pose estimation. The authors therefore propose a visual-servoing controlled robotic hand with RGB high-speed cameras. Two cameras have their own database in the system. Each data set has proportional information of each hand image and image features for matching, and joint angle data for output as estimated results. Once sequential hand images are recorded

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Guru, D. S., K. B. Nagasundara, S. Manjunath, and R. Dinesh. "An Approach for Hand Vein Representation and Indexing." International Journal of Digital Crime and Forensics 3, no. 2 (2011): 1–15. http://dx.doi.org/10.4018/jdcf.2011040101.

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This paper proposes a model for representing and indexing of hand vein images. The proposed representation model identifies the junction points and perceives the spatial relationships existing among all junction points in hand vein images by the use of triangular spatial relationship (TSR). The model preserves the TSR among the junction points in a symbolic hand vein image by the use of quadruples and for each quadruple, a unique TSR key is generated. A novel methodology to label the junction points based on graph properties of junction points is also proposed. A Symbolic Hand Vein Image Datab

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Dissertations / Theses on the topic "The image of hand"

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Chandrasekhar, Chaya. "Pāla-Period Buddha Images: their hands, hand gestures, and hand-held attributes." The Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=osu1092830047.

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Chandrasekhar, Chaya. "Påla-period Buddha images their hands, hand gestures, and hand-held attributes /." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1092830047.

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Thesis (Ph. D.)--Ohio State University, 2004.<br>Document formatted into pages; contains xvi,375 p.; also contains graphics. Includes bibliographical references. Abstract available online via OhioLINK's ETD Center; full text release delayed at author's request until 2009 Aug. 18.

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遲秉壯 and Ping-chong Chee. "Hand-printed Chinese character recognition and image preprocessing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31213972.

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Chee, Ping-chong. "Hand-printed Chinese character recognition and image preprocessing /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B18597579.

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Saremi, Shahrzad. "Evolutionary Hand Posture Estimation for Image-based Gesture Detection Systems." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/374748.

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Hand posture estimation is one of the main phases of hand gesture estimation. It refers to the process of estimating a real hand image obtained from an acquisition device in a computer. The accuracy of the estimated hand model has a direct impact on feature selection and classi cation. The current hand posture estimation techniques are divided into three classes: generative, discriminative, and hybrid methods. In the rst, a model of the hand is generated and improved to model a hand in a computer accurately. In the second class, a database of di erent hand images is created and used to estima

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Liu, Nianjun. "Hand gesture recognition by Hidden Markov Models /." [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18158.pdf.

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Banks, R. N. "Neural networks for hand-printed character recognition." Thesis, University of Nottingham, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.293655.

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Font, Aragonès Xavier. "Visible, near infrared and thermal hand-based image biometric recognition." Doctoral thesis, Universitat Politècnica de Catalunya, 2013. http://hdl.handle.net/10803/117685.

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Biometric Recognition refers to the automatic identification of a person based on his or her anatomical characteristic or modality (i.e., fingerprint, palmprint, face) or behavioural (i.e., signature) characteristic. It is a fundamental key issue in any process concerned with security, shared resources, network transactions among many others. Arises as a fundamental problem widely known as recognition, and becomes a must step before permission is granted. It is supposed that protects key resources by only allowing those resources to be used by users that have been granted authority to use or t

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McDonell, Margaret. "The invisible hand : cross-cultural influence on editorial practice /." St. Lucia, Qld, 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18021.pdf.

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Prokaj, Jan. "Scale Space Based Grammar for Hand Detection." Honors in the Major Thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/985.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.<br>Bachelors<br>Engineering and Computer Science<br>Computer Science

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Books on the topic "The image of hand"

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1930-, Kieffer René, and Bergman Jan, eds. La Main de Dieu =: Die Hand Gottes. Mohr, 1997.

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Dennis, Crompton, Henry David, Herbert Stephen, and Magic Lantern Society of Great Britain., eds. Magic images: The art of hand-painted and photographic lantern slides. Magic Lantern Society of Great Britain, 1990.

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Stein, Gertrude. Five short war poems: Five hand-drawn images by Matthew Tyson. Imprints, 1989.

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B, Barlow H., ed. Natural and artificial low-level seeing systems: Proceedings of a Royal Society Discussion Meeting held on 25 and 26 March 1992. Royal Society, 1993.

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Grenander, Ulf. Hands: A pattern theoretic study of biological shapes. Springer-Verlag, 1991.

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Hall, Toni-Ann. Notebook with Hand-Drawn Cover Image. Blurb, 2018.

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Book of Embroidery : Start Embroidery with Instructions and Image: Hand Embroidery Tutorials. Independently Published, 2021.

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WILLIAMS, Donald. Embroidery Ideas Tutorials : Start Embroidery with Instructions and Image: Hand Embroidery Tutorials. Independently Published, 2021.

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Greisdorf, Howard F., and Brian C. O'Connor. Structures of Image Collections. Libraries Unlimited, 2007. http://dx.doi.org/10.5040/9798216020134.

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Human beings have always had a penchant for collecting images. The challenge today is that almost anything and everything in the world is available as a viewable image. Consequently, say O'Connor and Greisdorf, image collections can no longer be the result of ad hoc processes rooted in antiquated methodologies. To this end, they present the reader with an interdisciplinary approach to the principles, practices and belief systems underlying categorization and image management. The book is divided into three parts: defining the nature of images; describing how images are used; and explaining how

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Dougherty, Edward R., and Roberto A. Lotufo. Hands-on Morphological Image Processing. SPIE, 2003. http://dx.doi.org/10.1117/3.501104.

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Book chapters on the topic "The image of hand"

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Schreyer, Lucia. "1.9 Hand-Stücke." In Image. transcript Verlag, 2022. http://dx.doi.org/10.14361/9783839454909-011.

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Chaudhary, Ankit. "Hand Image Segmentation." In Robust Hand Gesture Recognition for Robotic Hand Control. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4798-5_4.

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Viitaniemi, Ville, Matti Karppa, Jorma Laaksonen, and Tommi Jantunen. "Detecting Hand-Head Occlusions in Sign Language Video." In Image Analysis. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38886-6_35.

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Bera, Asish, Debotosh Bhattacharjee, and Mita Nasipuri. "Hand Biometric Verification with Hand Image-Based CAPTCHA." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8180-4_1.

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Kuronen, Toni, Tuomas Eerola, Lasse Lensu, Jari Takatalo, Jukka Häkkinen, and Heikki Kälviäinen. "High-Speed Hand Tracking for Studying Human-Computer Interaction." In Image Analysis. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19665-7_11.

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Riegler, Gernot, David Ferstl, Matthias Rüther, and Horst Bischof. "A Framework for Articulated Hand Pose Estimation and Evaluation." In Image Analysis. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19665-7_4.

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Fournier, Régis, and Amine Naït-Ali. "Introduction to Hand Biometrics." In Signal and Image Processing for Biometrics. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118561911.ch8.

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Gobbetti, Enrico, Riccardo Scateni, and Gianluigi Zanetti. "Head and Hand Tracking Devices in Virtual Reality." In 3D Image Processing. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-642-59438-0_26.

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Fudono, Kenji, Tomokazu Sato, and Naokazu Yokoya. "Interactive 3-D Modeling System Using a Hand-Held Video Camera." In Image Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11499145_126.

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Cordella, Francesca, Francesco Di Corato, Loredana Zollo, and Bruno Siciliano. "A Robust Hand Pose Estimation Algorithm for Hand Rehabilitation." In New Trends in Image Analysis and Processing – ICIAP 2013. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41190-8_1.

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Conference papers on the topic "The image of hand"

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Park, Jeongwoo, and Je Hyeong Hong. "HoloGesture: A Multimodal Dataset For Hand Gesture Recognition Robust To Hand Textures On Head-Mounted Mixed-Reality Devices." In 2024 IEEE International Conference on Image Processing (ICIP). IEEE, 2024. http://dx.doi.org/10.1109/icip51287.2024.10648161.

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Jiang, Hai, Yusuke Yamanoi, Peiji Chen, et al. "Postural Synergy Analysis of Continuous Hand Movements for Application to Prosthetic Hands." In 2024 17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI). IEEE, 2024. https://doi.org/10.1109/cisp-bmei64163.2024.10906163.

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Pohanková, Tereza, and Vilém Pechanec. "QUANTIFYING THE COOLING FUNCTION OF URBAN VEGETATION BASED ON IMAGE DATA ANALYSIS." In Public recreation and landscape protection - with environment hand in hand! Mendel University in Brno, 2024. http://dx.doi.org/10.11118/978-80-7509-963-1-0244.

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Lei, Tao, Rui Sun, Xuan Wang, Yingbo Wang, Xi He, and Asoke Nandi. "CiT-Net: Convolutional Neural Networks Hand in Hand with Vision Transformers for Medical Image Segmentation." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/113.

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The hybrid architecture of convolutional neural networks (CNNs) and Transformer are very popular for medical image segmentation. However, it suffers from two challenges. First, although a CNNs branch can capture the local image features using vanilla convolution, it cannot achieve adaptive feature learning. Second, although a Transformer branch can capture the global features, it ignores the channel and cross-dimensional self-attention, resulting in a low segmentation accuracy on complex-content images. To address these challenges, we propose a novel hybrid architecture of convolutional neural

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Mar-Or, Etay, and Pundik Dmitry. "Hand motion and image stabilization in hand-held devices." In Electronic Imaging 2008, edited by Susan P. Farnand and Frans Gaykema. SPIE, 2008. http://dx.doi.org/10.1117/12.762884.

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Saeed, Anwar, Robert Niese, Ayoub Al-Hamadi, and Bernd Michaelis. "Coping with hand-hand overlapping in bimanual movements." In 2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA). IEEE, 2011. http://dx.doi.org/10.1109/icsipa.2011.6144134.

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Baltruschat, Ivo Matteo, Axel Saalbach, Mattias P. Heinrich, Hannes Nickisch, and Sascha Jockel. "Orientation regression in hand radiographs: a transfer learning approach." In Image Processing, edited by Elsa D. Angelini and Bennett A. Landman. SPIE, 2018. http://dx.doi.org/10.1117/12.2291620.

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Suppatoomsin, Chompoo. "Hybrid method for hand segmentation." In Second International Conference on Digital Image Processing. SPIE, 2010. http://dx.doi.org/10.1117/12.856290.

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Iorpenda, Msuega, and Volker Willert. "Constrained hand-multiple-eyes calibration." In Forum Bildverarbeitung 2024 = Image Pocessing Forum 2024. KIT Scientific Publishing, 2024. https://doi.org/10.58895/ksp/1000174496-5.

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This paper addresses the problem of calibrating multiple visual sensors mounted on a robotic manipulator, a task critical for accurate robot perception and interaction. We present a novel approach to hand-multiple-eyes calibration that incorporates closed-loop constraints to ensure consistency between the sensors’ poses. Unlike traditional hand-eye calibration methods that handle individual sensor pairs independently, our method leverages a unified optimization framework that simultaneously optimizes the relative poses of all sensors while enforcing a loop closure constraint to each pose tripl

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Puttapirat, Pargorn, and Theekapun Charoenpong. "Hand posture estimation from 2D image sequence by hand landmark identification." In 2017 9th International Conference on Knowledge and Smart Technology (KST). IEEE, 2017. http://dx.doi.org/10.1109/kst.2017.7886088.

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Reports on the topic "The image of hand"

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Dunculin, Charles L. Hand-Held Probe MR Image-Guided Biopsy and Treatment of Prostate Cancer. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada391548.

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Dumoulin, Charles I. Hand-Held Probe for MR Image-Guided Biopsy and Treatment of Prostate Cancer. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada398211.

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Hinnrichs, Michele, James Jensen, and Gerard McAnally. Hand Held Hyperspectral Imager for Standoff Detection of Chemical and Biological Aerosols. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada512507.

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Erickson, Sarah J. A Novel Hand-Held Optical Imager with Real-Time Coregistration Facilities Toward Diagnostic Mammography. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada542735.

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Martin, Kathi, Nick Jushchyshyn, and Claire King. James Galanos, Silk Chiffon Afternoon Dress c. Fall 1976. Drexel Digital Museum, 2018. http://dx.doi.org/10.17918/q3g5-n257.

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The URL links to a website page in the Drexel Digital Museum (DDM) fashion image archive containing a 3D interactive panorama of an evening suit by American fashion designer James Galanos with related text. This afternoon dress is from Galanos' Fall 1976 collection. It is made from pale pink silk chiffon and finished with hand stitching on the hems and edges of this dress, The dress was gifted to Drexel University as part of The James G. Galanos Archive at Drexel University in 2016. After it was imaged the gown was deemed too fragile to exhibit. By imaging it using high resolution GigaPan tech

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Bhatt, Parth, Curtis Edson, and Ann MacLean. Image Processing in Dense Forest Areas using Unmanned Aerial System (UAS). Michigan Technological University, 2022. http://dx.doi.org/10.37099/mtu.dc.michigantech-p/16366.

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Imagery collected via Unmanned Aerial System (UAS) platforms has become popular in recent years due to improvements in a Digital Single-Lens Reflex (DSLR) camera (centimeter and sub-centimeter), lower operation costs as compared to human piloted aircraft, and the ability to collect data over areas with limited ground access. Many different application (e.g., forestry, agriculture, geology, archaeology) are already using and utilizing the advantages of UAS data. Although, there are numerous UAS image processing workflows, for each application the approach can be different. In this study, we dev

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Bolton, Laura. WASH in Schools for Student Return During the COVID-19 Pandemic. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/k4d.2021.024.

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The literature on WASH and school re-opening during the COVID-19 pandemic is dominated by guidelines with little in the way of recent evidence or lessons learned. Analysis of data from school re-openings at the end of 2020 suggests that with mitigation measures in place community infection rates should not be affected by children returning to school. Although children carry a lower risk of infection, they do have large numbers of contact in the school environment, so hygiene and distancing measures are important. The key guidelines for WASH in schools during the COVID-19 pandemic include: chil

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Niklander ribera, Gustavo. https://carver.university/academiccrit/art-gustavo-nikklander/. Carver University; Universidad Autónoma de Chile, 2025. https://doi.org/10.32457/niklander22025103.

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The emergence of artificial intelligence (AI) in the workplace has raised numerous questions. On the one hand, its ability to increase efficiency and relieve people of routine tasks is widely celebrated. On the other hand, there is growing concern about the role humans will play when machines not only execute tasks but also create, respond, and decide. In this new scenario, soft skills are often proposed as a possible answer—but not without significant challenges. In an environment where algorithms can already write texts, generate images, serve customers, and solve operational problems, it is

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Burbano Figueroa, Oscar, Milena Moreno Moran, Lorena Osorio Almanza, et al. Identification of resistance to ramulosis caused by Colletotrichum gossypii var. cephalosporioides in cotton advanced breeding lines and monitoring of ramulosis disease by RGB-image analysis. Corporación Colombiana de Investigación Agropecuaria - AGROSAVIA, 2016. http://dx.doi.org/10.21930/agrosavia.informe.2016.2.

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Identification of resistance to ramulosis caused by Colletotrichum gossypii var. cephalosporioides in cotton advanced breeding lines and monitoring of ramulosis disease by RGB-image analysis Abstract Cotton growing regions in South America are affected by Colletotrichum gossypii var. cephalosporioides (Cgc). The most severe epidemics provokes considerable yield reductions linked to meristem necrosis, oversprouting, excessive branching and stunting (Figure 1). The Sinu Valley is a major cotton producer in Colombia and is heavily affected by this disease. Rainfall was identified as the main driv

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Go, Eugenia, Kentaro Nakajima, Yasuyuki Sawada, and Kiyoshi Taniguchi. On the Use of Satellite-Based Vehicle Flows Data to Assess Local Economic Activity: The Case of Philippine Cities. Asian Development Bank, 2022. http://dx.doi.org/10.22617/wps220079-2.

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Satellite image-derived vehicle counts were used to measure local economic activity following the opening of the new terminal at the Mactan-Cebu International Airport in the Philippines. Results reveal that the terminal’s opening has had positive impacts on Cebu’s local economy. A comparison of the vehicle count measure with luminosity-derived metrics suggests that the former is better at capturing seasonal and spatial variations in treatment effects, especially for beach tourism activities in Cebu.

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