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Статті в журналах з теми "Video image analysi"
Alothman, Raya Basil, Imad Ibraheem Saada, and Basma Salim Bazel Al-Brge. "A Performance-Based Comparative Encryption and Decryption Technique for Image and Video for Mobile Computing." Journal of Cases on Information Technology 24, no. 2 (April 2022): 1–18. http://dx.doi.org/10.4018/jcit.20220101.oa1.
Повний текст джерелаDeng, Zhaopeng, Maoyong Cao, Yushui Geng, and Laxmisha Rai. "Generating a Cylindrical Panorama from a Forward-Looking Borehole Video for Borehole Condition Analysis." Applied Sciences 9, no. 16 (August 20, 2019): 3437. http://dx.doi.org/10.3390/app9163437.
Повний текст джерелаLivingston, Merlin L. M., and Agnel L. G. X. Livingston. "Processing of Images and Videos for Extracting Text Information from Clustered Features Using Graph Wavelet Transform." Journal of Computational and Theoretical Nanoscience 16, no. 2 (February 1, 2019): 557–61. http://dx.doi.org/10.1166/jctn.2019.7768.
Повний текст джерелаGuo, Jianbang, Peng Sun, and Sang-Bing Tsai. "A Study on the Optimization Simulation of Big Data Video Image Keyframes in Motion Models." Wireless Communications and Mobile Computing 2022 (March 16, 2022): 1–12. http://dx.doi.org/10.1155/2022/2508174.
Повний текст джерелаAparna, RR. "Swarm Intelligence for Automatic Video Image Contrast Adjustment." International Journal of Rough Sets and Data Analysis 3, no. 3 (July 2016): 21–37. http://dx.doi.org/10.4018/ijrsda.2016070102.
Повний текст джерелаKim, Jie-Hyun, Sang-Il Oh, So-Young Han, Ji-Soo Keum, Kyung-Nam Kim, Jae-Young Chun, Young-Hoon Youn, and Hyojin Park. "An Optimal Artificial Intelligence System for Real-Time Endoscopic Prediction of Invasion Depth in Early Gastric Cancer." Cancers 14, no. 23 (December 5, 2022): 6000. http://dx.doi.org/10.3390/cancers14236000.
Повний текст джерелаXu, Longcheng, Deokhwan Choi, and Zeyun Yang. "Deep Neural Network-Based Sports Marketing Video Detection Research." Scientific Programming 2022 (March 19, 2022): 1–7. http://dx.doi.org/10.1155/2022/8148972.
Повний текст джерелаGuangyu, Han. "Analysis of Sports Video Intelligent Classification Technology Based on Neural Network Algorithm and Transfer Learning." Computational Intelligence and Neuroscience 2022 (March 24, 2022): 1–10. http://dx.doi.org/10.1155/2022/7474581.
Повний текст джерелаLokkondra, Chaitra Yuvaraj, Dinesh Ramegowda, Gopalakrishna Madigondanahalli Thimmaiah, Ajay Prakash Bassappa Vijaya, and Manjula Hebbaka Shivananjappa. "ETDR: An Exploratory View of Text Detection and Recognition in Images and Videos." Revue d'Intelligence Artificielle 35, no. 5 (October 31, 2021): 383–93. http://dx.doi.org/10.18280/ria.350504.
Повний текст джерелаYao-DongWang, Idaku Ishii, Takeshi Takaki, and Kenji Tajima. "An Intelligent High-Frame-Rate Video Logging System for Abnormal Behavior Analysis." Journal of Robotics and Mechatronics 23, no. 1 (February 20, 2011): 53–65. http://dx.doi.org/10.20965/jrm.2011.p0053.
Повний текст джерелаДисертації з теми "Video image analysi"
GIACHELLO, SILVIA. "Identità' e memoria visuale: comunità', eventi, documentazione." Doctoral thesis, Politecnico di Torino, 2012. http://hdl.handle.net/11583/2540089.
Повний текст джерелаDye, Brigham R. "Reliability of pre-service teachers' coding of teaching videos using a video-analysis tool /." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2020.pdf.
Повний текст джерелаKim, Tae-Kyun. "Discriminant analysis of patterns in images, image ensembles, and videos." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612084.
Повний текст джерелаSdiri, Bilel. "2D/3D Endoscopic image enhancement and analysis for video guided surgery." Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCD030.
Повний текст джерелаMinimally invasive surgery has made remarkable progress in the last decades and became a very popular diagnosis and treatment tool, especially with the rapid medical and technological advances leading to innovative new tools such as robotic surgical systems and wireless capsule endoscopy. Due to the intrinsic characteristics of the endoscopic environment including dynamic illumination conditions and moist tissues with high reflectance, endoscopic images suffer often from several degradations such as large dark regions,with low contrast and sharpness, and many artifacts such as specular reflections and blur. These challenges together with the introduction of three dimensional(3D) imaging surgical systems have prompted the question of endoscopic images quality, which needs to be enhanced. The latter process aims either to provide the surgeons/doctors with a better visual feedback or improve the outcomes of some subsequent tasks such as features extraction for 3D organ reconstruction and registration. This thesis addresses the problem of endoscopic image quality enhancement by proposing novel enhancement techniques for both two-dimensional (2D) and stereo (i.e. 3D)endoscopic images.In the context of automatic tissue abnormality detection and classification for gastro-intestinal tract disease diagnosis, we proposed a pre-processing enhancement method for 2D endoscopic images and wireless capsule endoscopy improving both local and global contrast. The proposed method expose inner subtle structures and tissues details, which improves the features detection process and the automatic classification rate of neoplastic,non-neoplastic and inflammatory tissues. Inspired by binocular vision attention features of the human visual system, we proposed in another workan adaptive enhancement technique for stereo endoscopic images combining depth and edginess information. The adaptability of the proposed method consists in adjusting the enhancement to both local image activity and depth level within the scene while controlling the interview difference using abinocular perception model. A subjective experiment was conducted to evaluate the performance of the proposed algorithm in terms of visual qualityby both expert and non-expert observers whose scores demonstrated the efficiency of our 3D contrast enhancement technique. In the same scope, we resort in another recent stereo endoscopic image enhancement work to the wavelet domain to target the enhancement towards specific image components using the multiscale representation and the efficient space-frequency localization property. The proposed joint enhancement methods rely on cross-view processing and depth information, for both the wavelet decomposition and the enhancement steps, to exploit the inter-view redundancies together with perceptual human visual system properties related to contrast sensitivity and binocular combination and rivalry. The visual qualityof the processed images and objective assessment metrics demonstrate the efficiency of our joint stereo enhancement in adjusting the image illuminationin both dark and saturated regions and emphasizing local image details such as fine veins and micro vessels, compared to other endoscopic enhancement techniques for 2D and 3D images
Li, Dong. "Thermal image analysis using calibrated video imaging." Diss., Columbia, Mo. : University of Missouri-Columbia, 2006. http://hdl.handle.net/10355/4455.
Повний текст джерелаThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 23, 2009) Includes bibliographical references.
Eastwood, Brian S. Taylor Russell M. "Multiple layer image analysis for video microscopy." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2009. http://dc.lib.unc.edu/u?/etd,2813.
Повний текст джерелаTitle from electronic title page (viewed Mar. 10, 2010). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science." Discipline: Computer Science; Department/School: Computer Science.
Sheikh, Faridul Hasan. "Analysis of 3D color matches for the creation and consumption of video content." Thesis, Saint-Etienne, 2014. http://www.theses.fr/2014STET4001.
Повний текст джерелаThe objective of this thesis is to propose a solution to the problem of color consistency between images originate from the same scene irrespective of acquisition conditions. Therefore, we present a new color mapping framework that is able to compensate color differences and achieve color consistency between views of the same scene. Our proposed, new framework works in two phases. In the first phase, we propose a new method that can robustly collect color correspondences from the neighborhood of sparse feature correspondences, despite the low accuracy of feature correspondences. In the second phase, from these color correspondences, we introduce a new, two-step, robust estimation of the color mapping model: first, nonlinear channel-wise estimation; second, linear cross-channel estimation. For experimental assessment, we propose two new image datasets: one with ground truth for quantitative assessment; another, without the ground truth for qualitative assessment. We have demonstrated a series of experiments in order to investigate the robustness of our proposed framework as well as its comparison with the state of the art. We have also provided brief overview, sample results, and future perspectives of various applications of color mapping. In experimental results, we have demonstrated that, unlike many methods of the state of the art, our proposed color mapping is robust to changes of: illumination spectrum, illumination intensity, imaging devices (sensor, optic), imaging device settings (exposure, white balance), viewing conditions (viewing angle, viewing distance)
Lee, Sangkeun. "Video analysis and abstraction in the compressed domain." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04072004-180041/unrestricted/lee%5fsangkeun%5f200312%5fphd.pdf.
Повний текст джерелаGuo, Y. (Yimo). "Image and video analysis by local descriptors and deformable image registration." Doctoral thesis, Oulun yliopisto, 2013. http://urn.fi/urn:isbn:9789526201412.
Повний текст джерелаTiivistelmä Kuvan deskriptiolla on tärkeä rooli staattisissa kuvissa esiintyvien luontaisten kokonaisuuksien ja näkymien kuvaamisessa. Viime vuosikymmeninä se on tullut perustavaa laatua olevaksi ongelmaksi monissa käytännön konenäön tehtävissä, kuten tekstuurien luokittelu, kasvojen tunnistaminen, materiaalien luokittelu ja lääketieteellisten kuvien analysointi. Staattisen kuva-analyysin tutkimusala voidaan myös laajentaa videoanalyysiin, kuten dynaamisten tekstuurien tunnistukseen, luokitteluun ja synteesiin. Tämä väitöskirjatutkimus myötävaikuttaa kuva- ja videoanalyysin tutkimukseen ja kehittymiseen kahdesta näkökulmasta. Työn ensimmäisessä osassa esitetään kaksi kuvan deskriptiomenetelmää erottelukykyisten esitystapojen luomiseksi kuvien luokitteluun. Ne suunnitellaan ohjaamattomiksi (eli tekstuurikuvien luokkien leimoja ei ole käytettävissä) tai ohjatuiksi (eli luokkien leimat ovat saatavilla). Aluksi kehitetään ohjattu malli oppimaan erottelukykyisiä paikallisia kuvioita, mikä formuloi kuvan deskriptiomenetelmän integroituna kolmikerroksisena mallina - tavoitteena estimoida optimaalinen kiinnostavien kuvioiden alijoukko ottamalla samanaikaisesti huomioon piirteiden robustisuus, erottelukyky ja esityskapasiteetti. Seuraavaksi, sellaisia tapauksia varten, joissa luokkaleimoja ei ole saatavilla, esitetään työssä lineaarinen konfiguraatiomalli kuvaamaan kuvan mikroskooppisia rakenteita ohjaamattomalla tavalla. Tätä käytetään sitten yhdessä paikallisen kuvaajan, eli local binary pattern (LBP) –operaattorin kanssa. Teoreettisella tarkastelulla osoitetaan kehitetyn kuvaajan olevan rotaatioinvariantti ja kykenevän tuottamaan erottelukykyistä, täydentävää informaatiota perinteiselle LBP-menetelmälle. Työn toisessa osassa tutkitaan videoanalyysiä, perustuen staattisen kuvan deskriptioon ja deformoituvaan kuvien rekisteröintiin – sovellusaloina dynaamisten tekstuurien kuvaaminen, synteesi ja tunnistaminen. Aluksi ehdotetaan sellainen malli dynaamisten tekstuurien synteesiin, joka luo jatkuvan ja äärettömän kuvien virran annetusta äärellisen mittaisesta videosta. Menetelmä liittää yhteen videon pätkiä aika-avaruudessa valitsemalla keskenään yhteensopivia kuvakehyksiä videosta ja järjestämällä ne loogiseen järjestykseen. Seuraavaksi työssä esitetään sellainen uusi menetelmä kasvojen ilmeiden tunnistukseen, joka formuloi dynaamisen kasvojen ilmeiden tunnistusongelman pitkittäissuuntaisten kartastojen rakentamisen ja ryhmäkohtaisen kuvien rekisteröinnin ongelmana
Stobaugh, John David. "Novel use of video and image analysis in a video compression system." Thesis, University of Iowa, 2015. https://ir.uiowa.edu/etd/1766.
Повний текст джерелаКниги з теми "Video image analysi"
Tokan-Lawal, Folashade. Quantitative image analysis of video images of the larynx. Manchester: UMIST, 1998.
Знайти повний текст джерелаTian, Jing, and Li Chen. Intelligent image and video interpretation: Algorithms and applications. Hershey, PA: Information Science Reference, 2013.
Знайти повний текст джерелаC, Kotropoulos, and Pitas I, eds. Nonlinear model-based image/video processing and analysis. New York: Wiley, 2001.
Знайти повний текст джерелаImage and video processing in the compressed domain. Boca Raton: CRC Press, 2011.
Знайти повний текст джерелаSubhasis, Chaudhuri, and SpringerLink (Online service), eds. Video Analysis and Repackaging for Distance Education. New York, NY: Springer New York, 2012.
Знайти повний текст джерелаCamastra, Francesco, and Alessandro Vinciarelli. Machine Learning for Audio, Image and Video Analysis. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-6735-8.
Повний текст джерелаCamastra, Francesco, and Alessandro Vinciarelli. Machine Learning for Audio, Image and Video Analysis. London: Springer London, 2008. http://dx.doi.org/10.1007/978-1-84800-007-0.
Повний текст джерелаContent-based analysis of digital video. Boston, MA: Kluwer Academic Publishers, 2004.
Знайти повний текст джерелаKwaśnicka, Halina, and Lakhmi C. Jain, eds. Bridging the Semantic Gap in Image and Video Analysis. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73891-8.
Повний текст джерелаRandall, Reed Todd, ed. Digital image sequence processing, compression, and analysis. Boca Raton: CRC Press, 2005.
Знайти повний текст джерелаЧастини книг з теми "Video image analysi"
Söderström, Ulrik, and Haibo Li. "High Definition Wearable Video Communication." In Image Analysis, 500–512. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02230-2_51.
Повний текст джерелаDouze, Matthijs, and Vincent Charvillat. "Real-Time Tracking of Video Sequences in a Panoramic View for Object-Based Video Coding." In Image Analysis, 1022–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_134.
Повний текст джерелаUegaki, Naoki, Masao Izumi, and Kunio Fukunaga. "Multimodal Automatic Indexing for Broadcast Soccer Video." In Image Analysis, 802–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11499145_81.
Повний текст джерелаLuzardo, Marcos, Matti Karppa, Jorma Laaksonen, and Tommi Jantunen. "Head Pose Estimation for Sign Language Video." In Image Analysis, 349–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38886-6_34.
Повний текст джерелаWalter, Robert J., and Michael W. Berns. "Digital Image Processing and Analysis." In Video Microscopy, 327–92. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4757-6925-8_10.
Повний текст джерелаPaalanen, Pekka, Joni-Kristian Kämäräinen, and Heikki Kälviäinen. "Image Based Quantitative Mosaic Evaluation with Artificial Video." In Image Analysis, 470–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02230-2_48.
Повний текст джерелаKoskela, Markus, Mats Sjöberg, and Jorma Laaksonen. "Improving Automatic Video Retrieval with Semantic Concept Detection." In Image Analysis, 480–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02230-2_49.
Повний текст джерелаSlot, Kristine, René Truelsen, and Jon Sporring. "Content-Aware Video Editing in the Temporal Domain." In Image Analysis, 490–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02230-2_50.
Повний текст джерелаLundmark, Astrid, and Leif Haglund. "Adaptive Spatial and Temporal Prefiltering for Video Compression." In Image Analysis, 953–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_125.
Повний текст джерелаBräuer-Burchardt, Christian. "Detection of Strong Shadows in Monochromatic Video Streams." In Image Analysis, 646–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_86.
Повний текст джерелаТези доповідей конференцій з теми "Video image analysi"
Fullerton, Anne M., Thomas C. Fu, David A. Drazen, and Don C. Walker. "Analysis Methods for Vessel Generated Spray." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-31313.
Повний текст джерелаЗвездакова, Анастасия, Anastasia Zvezdakova, Дмитрий Куликов, Dmitriy Kulikov, Денис Кондранин, Denis Kondranin, Дмитрий Ватолин, and Dmitriy Vatolin. "Barriers Towards No-reference Metrics Application to Compressed Video Quality Analysis: on the Example of No-reference Metric NIQE." In 29th International Conference on Computer Graphics, Image Processing and Computer Vision, Visualization Systems and the Virtual Environment GraphiCon'2019. Bryansk State Technical University, 2019. http://dx.doi.org/10.30987/graphicon-2019-2-22-27.
Повний текст джерелаLima, Karim Ferreira, Rodrigo Marques de Figueiredo, Eduardo Augusto Martins, and Jean Schmith. "Virtual lines for offside situations analysis in football." In Anais Estendidos da Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/sibgrapi.est.2021.20037.
Повний текст джерелаDimitriu, Anda. "TEACHING ENGLISH IN A DIGITAL WORLD: THE ADVANTAGES AND DISADVANTAGES OF INTRODUCING VIDEOS IN ENGLISH LANGUAGE COURSES." In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-214.
Повний текст джерелаMacHuchon, Keith R., Wehan J. Wessels, Chin H. Wu, and Paul C. Liu. "The Use of Streamed Digital Video Data and Binocular Stereoscopic Image System (BiSIS) Processing Methods to Analyze Ocean Wave Field Kinematics." In ASME 2009 28th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/omae2009-79853.
Повний текст джерелаGuo, Shenghan, Dali Wang, Jian Chen, Zhili Feng, and Weihong “Grace” Guo. "Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-61775.
Повний текст джерелаShou, Yu-Wen. "Intelligent Judgment System for Vehicle-Overtaking by Motion Detection in Subsequent Images." In ASME 2009 International Mechanical Engineering Congress and Exposition. ASMEDC, 2009. http://dx.doi.org/10.1115/imece2009-10922.
Повний текст джерелаImai, Seira, Yasuharu Nakajima, and Motohiko Murai. "Experimental Study on Bubble Size Measurement for Development of Seafloor Massive Sulfides." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95186.
Повний текст джерелаIvanov, Oleg, Alexey Danilovich, Vyacheslav Stepanov, Sergey Smirnov, and Victor Potapov. "Remote Measurements of Radioactivity Distribution With BROKK Robotic System." In ASME 2009 12th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2009. http://dx.doi.org/10.1115/icem2009-16147.
Повний текст джерелаHsu, Fu Kuo, Eddy C. Tam, Taiwei Lu, Francis T. S. Yu, Eiichiro Nishihara, and Takashi Nishikawa. "Implementation and analysis of optical-disk-based joint-transform correlators." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.thii2.
Повний текст джерелаЗвіти організацій з теми "Video image analysi"
Bandat, N. E. Video image analysis using the Selective Video Processor development platform. Office of Scientific and Technical Information (OSTI), August 1989. http://dx.doi.org/10.2172/6161006.
Повний текст джерелаLiang, Yiqing. Video Retrieval Based on Language and Image Analysis. Fort Belvoir, VA: Defense Technical Information Center, May 1999. http://dx.doi.org/10.21236/ada364129.
Повний текст джерелаBovik, Alan C. AM-FM Analysis of Images and Video. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada387139.
Повний текст джерелаBrumby, Steven P. Video Analysis & Search Technology (VAST): Automated content-based labeling and searching for video and images. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1133765.
Повний текст джерелаRigotti, Christophe, and Mohand-Saïd Hacid. Representing and Reasoning on Conceptual Queries Over Image Databases. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.89.
Повний текст джерелаRigotti, Christophe, and Mohand-Saïd Hacid. Representing and Reasoning on Conceptual Queries Over Image Databases. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.89.
Повний текст джерелаSapiro, Guillermo. Structured and Collaborative Signal Models: Theory and Applications in Image, Video, and Audio Analysis. Fort Belvoir, VA: Defense Technical Information Center, January 2013. http://dx.doi.org/10.21236/ada586672.
Повний текст джерелаJerosch, K., A. Luedtke, P. Pledge, O. Paitich, and V E Kostylev. Automatic image analysis of sediment types: mapping from georeferenced video footage on the Labrador Shelf. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2011. http://dx.doi.org/10.4095/288055.
Повний текст джерелаBaluk, Nadia, Natalia Basij, Larysa Buk, and Olha Vovchanska. VR/AR-TECHNOLOGIES – NEW CONTENT OF THE NEW MEDIA. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11074.
Повний текст джерелаPikilnyak, Andrey V., Nadia M. Stetsenko, Volodymyr P. Stetsenko, Tetiana V. Bondarenko, and Halyna V. Tkachuk. Comparative analysis of online dictionaries in the context of the digital transformation of education. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4431.
Повний текст джерела