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Relevant bibliographies by topics / Adaptive video coding

Academic literature on the topic 'Adaptive video coding'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "Adaptive video coding"

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Pan, Tung-Ming, Kuo-Chin Fan, and Yuan-Kai Wang. "Object-Based Approach for Adaptive Source Coding of Surveillance Video." Applied Sciences 9, no. 10 (May 16, 2019): 2003. http://dx.doi.org/10.3390/app9102003.

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Intelligent analysis of surveillance videos over networks requires high recognition accuracy by analyzing good-quality videos that however introduce significant bandwidth requirement. Degraded video quality because of high object dynamics under wireless video transmission induces more critical issues to the success of smart video surveillance. In this paper, an object-based source coding method is proposed to preserve constant quality of video streaming over wireless networks. The inverse relationship between video quality and object dynamics (i.e., decreasing video quality due to the occurrence of large and fast-moving objects) is characterized statistically as a linear model. A regression algorithm that uses robust M-estimator statistics is proposed to construct the linear model with respect to different bitrates. The linear model is applied to predict the bitrate increment required to enhance video quality. A simulated wireless environment is set up to verify the proposed method under different wireless situations. Experiments with real surveillance videos of a variety of object dynamics are conducted to evaluate the performance of the method. Experimental results demonstrate significant improvement of streaming videos relative to both visual and quantitative aspects.

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Fu, Zhe. "Embedded Image and Video Coding Algorithm Based on Adaptive Filtering Equation." Advances in Mathematical Physics 2021 (September 8, 2021): 1–11. http://dx.doi.org/10.1155/2021/7953993.

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Based on the improved adaptive filtering method, this paper conducts in-depth discussion and research on embedded graphics and video coding and chooses to improve the adaptive filtering algorithm from three aspects: starting point prediction, search template, and window partitioning. The algorithm is imported into the encoder for video capture and encoding. By capturing videos of different formats, resolutions, and times, the memory size of the video files collected before and after the algorithm optimization is compared, and the optimized algorithm occupies the memory space of the video file in the actual system. The conclusion of less and higher coding rates. The collected video information is stored on a personal computer equipped with a freeness, and external electronic devices only need to download and install the browser, and the collected video information can be accessed in the local area network through the protocol. The improved coding algorithm has higher coding efficiency and can reduce the storage space occupied by the video.

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Tu, Wang, Xin Jin, Lingjun Li, Chenggang Yan, Yaoqi Sun, Mang Xiao, Weidong Han, and Jiyong Zhang. "Efficient Content Adaptive Plenoptic Video Coding." IEEE Access 8 (2020): 5797–804. http://dx.doi.org/10.1109/access.2020.2964056.

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Yamaguchi, H. "Adaptive DCT coding of video signals." IEEE Transactions on Communications 41, no. 10 (1993): 1534–43. http://dx.doi.org/10.1109/26.237888.

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Hu, Qiang, Jun Zhou, Xiaoyun Zhang, Zhiru Shi, and Zhiyong Gao. "Viewport-adaptive 360-degree video coding." Multimedia Tools and Applications 79, no. 17-18 (January 13, 2020): 12205–26. http://dx.doi.org/10.1007/s11042-019-08390-7.

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Tsai, Chia-Yang, Ching-Yeh Chen, Tomoo Yamakage, In Suk Chong, Yu-Wen Huang, Chih-Ming Fu, Takayuki Itoh, et al. "Adaptive Loop Filtering for Video Coding." IEEE Journal of Selected Topics in Signal Processing 7, no. 6 (December 2013): 934–45. http://dx.doi.org/10.1109/jstsp.2013.2271974.

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KIM, Kyung-Yong, Gwang-Hoon PARK, and Doug-Young SUH. "Adaptive Depth-Map Coding for 3D-Video." IEICE Transactions on Information and Systems E93-D, no. 8 (2010): 2262–72. http://dx.doi.org/10.1587/transinf.e93.d.2262.

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Yoon, Yeo-Jin, Seung-Won Jung, Hahyun Lee, Hui Yong Kim, Jin Soo Choi, and Sung-Jea Ko. "Adaptive Prediction Block Filter for Video Coding." ETRI Journal 34, no. 1 (February 2, 2012): 106–9. http://dx.doi.org/10.4218/etrij.12.0211.0042.

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Dong, Jie, and Yan Ye. "Adaptive Downsampling for High-Definition Video Coding." IEEE Transactions on Circuits and Systems for Video Technology 24, no. 3 (March 2014): 480–88. http://dx.doi.org/10.1109/tcsvt.2013.2278146.

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Zhang, Yixuan, and Ce Zhu. "Adaptive coset partition for distributed video coding." Signal Processing 90, no. 8 (August 2010): 2480–86. http://dx.doi.org/10.1016/j.sigpro.2010.02.001.

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Dissertations / Theses on the topic "Adaptive video coding"

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Hosking, Brett. "Adaptive resolution video coding." Thesis, University of Bristol, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.707749.

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Su, Jonathan K. "Adaptive rate-constrained transform video coding." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/13364.

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Abrahamsson, Anna. "Variance Adaptive Quantization and Adaptive Offset Selection in High Efficiency Video Coding." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-278155.

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Video compression uses encoding to reduce the number of bits that are used forrepresenting a video file in order to store and transmit it at a smaller size. Adecoder reconstructs the received data into a representation of the original video.Video coding standards determines how the video compression should beconducted and one of the latest standards is High Efficiency Video Coding (HEVC).One technique that can be used in the encoder is variance adaptive quantizationwhich improves the subjective quality in videos. The technique assigns lowerquantization parameter values to parts of the frame with low variance to increasequality, and vice versa. Another part of the encoder is the sample adaptive offsetfilter, which reduces pixel errors caused by the compression. In this project, thevariance adaptive quantization technique is implemented in the Ericsson researchHEVC encoder c65. Its functionality is verified by subjective evaluation. It isinvestigated if the sample adaptive offset can exploit the adjusted quantizationparameters values when reducing pixel errors to improve compression efficiency. Amodel for this purpose is developed and implemented in c65. Data indicates thatthe model can increase the error reduction in the sample adaptive offset. However,the difference in performance of the model compared to a reference encoder is notsignificant.

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Jónsson, Ragner H. "Adaptive subband coding of video using probability distribution models." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/14453.

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Gu, Ye. "Wavelet-based adaptive video coding for packet-switching networks." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/37021.

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Chung, Wilson C. "Adaptive subband video coding in a rate-distortion-constrained framework." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/15459.

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De, La Rocha Gomes-Arevalillo Alfonso. "Investigating the Adaptive Loop Filter in Next Generation Video Coding." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-201141.

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Current trends on video technologies and services are demanding higher bit rates, highervideo resolutions and better video qualities. This issue results in the need of a new generationof video coding techniques to increase the quality and compression rates of previous standards.Since the release of HEVC, ITU-T VCEG and ISO/IEC MPEG have been studying the potentialneed for standardization of future video coding technologies with a compression capability thatsignificantly exceeds the ones from current standards. These new e↵orts of standardization andcompression enhancements are being implemented and evaluated over a software test modelknown under the name of Joint Exploration Model (JEM). One of the blocks being explored inJEM is an Adaptive Loop Filter (ALF) at the end of each frame’s processing flow. ALF aimsto minimize the error between original pixels and decoded pixels using Wiener-based adaptivefilter coefficients, reporting, in its JEM’s implementation, improvements of around a 1% in theBD MS-SSIM rate. A lot of e↵orts have been devoted on improving this block over the pastyears. However, current ALF implementations do not consider the potential use of adaptive QPalgorithms at the encoder. Adaptive QP algorithms enable the use of di↵erent quality levels forthe coding of di↵erent parts of a frame to enhance its subjective quality.In this thesis, we explore potential improvements over di↵erent dimensions of JEM’s AdaptiveLoop Filter block considering the potential use of adaptive QP algorithms. In the document, weexplore a great gamut of modification over ALF processing stages, being the ones with betterresults (i) a QP-aware implementation of ALF were the filter coefficients estimation, the internalRD-optimization and the CU-level flag decision process are optimized for the use of adaptiveQP, (ii) the optimization of ALF’s standard block activity classification stage through the useof CU-level information given by the di↵erent QPs used in a frame, and (iii) the optimizationof ALF’s standard block activity classification stage in B-frames through the application of acorrection weight on coded, i.e. not predicted, blocks of B-frames. These ALF modificationscombined obtained improvements of a 0.419% on average for the BD MS-SSIM rate in the lumachannel, showing each modification individual improvements of a 0.252%, 0.085% and 0.082%,respectively. Thus, we concluded the importance of optimizing ALF for the potential use ofadaptive-QP algorithms in the encoder, and the benefits of considering CU-level and frame-levelmetrics in ALF’s block classification stage.
Utvecklingen inom video-teknologi och service kräver högre bithastighet, högre videoupplösningoch bättre kvalitet. Problemet kräver en ny generation av kodning och tekniker för att ökakvaliteten och komprimeringsgraden utöver vad tidigare teknik kunnat prestera. Sedan lanseringenav HEVC har ITU-T VCEG och ISO/IEC MPEG studerat ett eventuellt behov av standardiseringav framtida video-kodings tekniker med kompressions kapacitet som vida överstigerdagens system. Dessa försök till standardisering och kompressionsframsteg har implementeratsoch utvärderats inom ramen för en mjukvara testmodell som kallas Joint Exploration Model(JEM). Ett av områdena som undersöks inom ramen för JEM är adaptiva loopfilter (ALF) somläggs till i slutet av varje bilds processflöde. ALF har som mål att minimera felet mellan originalpixel och avkodad pixel genom Wiener-baserade adaptiva filter-koefficienter. Mycket kraft harlagts på att förbättra detta område under de senaste åren. Men, nuvarande ALF-appliceringbeaktar inte potentialen av att använda adaptiva QP algoritmer i videokodaren. Adaptiva QPalgoritmer tillåter användningen av olika kvalitet på kodning av olika delar av bilden för attförbättra den subjektiva kvaliteten.I föreliggande uppsats kommer vi undersöka den potentiella förbättringen av JEM:s adaptivaloopfilter som kan uppnås genom att använda adaptiva QP algoritmer. I uppsatsen kommervi undersöka ett stort antal modifikationer i ALF:s process-stadier, för att ta reda på vilkenmodifikationer som har bäst resultat: (i) en QP-medveten implementering av ALF där filterkoefficientensuppskattning av den interna RD-optimeringen och CU-nivåns flaggbeslutsprocessär optimerade för användnngen av adaptiv QP, (ii) optimeringen av ALF:s standard blockaktivitets klassificerings stadie genom användning av CU-nivå-information producerad av deolika QP:n som används i en bild, och (iii) optimeringen av ALF:s standard block aktivitetsklassificerings stadier i B-bilders genom applicering av en korrektursvikt i tidigare kod, d.v.sej förutsedda, block av B-bilder. När dessa ALF modifikationer kombinerades förbättradesi genomsnitt BD MS-SSIM hastigheten i luma kanalen med 0.419%, där varje modifikationförbättrade med 0.252%, 0.085% och 0.082% var. Därigenom drog vi slutstatsen att det är viktigtatt optimera ALF för det potentiella användandet av adaptiva QP-algoritmer i kodaren, ochfördelarna av att beakta CU-nivåmätningar och bild-nivåmätningar i ALF:s block klassificeringsstadie.

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MORALES, FIGUEROA AMPARITO ALEXANDRA. "Adaptive Video Coding to Optimize Video Streaming in Internet and Wireless Ad-hoc Networks." Doctoral thesis, Università degli studi di Pavia, 2017. http://hdl.handle.net/11571/1203302.

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Abraham, Arun S. "Bandwidth-aware video transmission with adaptive image scaling." [Gainesville, Fla.] : University of Florida, 2003. http://purl.fcla.edu/fcla/etd/UFE0001221.

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Shu, Yan. "Coding of motion picture residues without adaptive spatial transforms." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0030/MQ47477.pdf.

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Books on the topic "Adaptive video coding"

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Xiao, Leping. Adaptive subband coding of full motion video with band restoration. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1993.

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Michel, Kieffer, and ScienceDirect (Online service), eds. Joint source-channel decoding: A cross-layer perspective with application in video broadcasting. London: Academic, 2009.

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Kieffer, Michel, and Pierre Duhamel. Joint Source-Channel Decoding: A Cross-Layer Perspective with Applications in Video Broadcasting. Elsevier Science & Technology Books, 2009.

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Book chapters on the topic "Adaptive video coding"

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Liu, Changdong, Yong Xie, Myung J. Lee, and Tarek N. Saadawi. "Adaptive Synchronization in Real-Time Multimedia Applications." In Multimedia Communications and Video Coding, 147–56. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0403-6_19.

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Wu, Jian, Yongfang Wang, Yun Zhu, and Yuan Shuai. "Adaptive Coding for Compressed Video Sensing." In Lecture Notes in Computer Science, 197–205. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71589-6_18.

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Kok, C. W., and Tsuhan Chen. "Video Coding with Adaptive Block Update." In Mobile Multimedia Communications, 301–8. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-0151-4_36.

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Ma, Siwei, Li Zhang, Xinfeng Zhang, and Wen Gao. "Block Adaptive Super Resolution Video Coding." In Advances in Multimedia Information Processing - PCM 2009, 1048–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10467-1_101.

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Campbell, Andrew, Alexandros Eleftheriadis, and Cristina Aurrecoechea. "End-to-End QoS Management for Adaptive Video Flows." In Multimedia Communications and Video Coding, 105–15. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0403-6_14.

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Corrêa, Guilherme, Pedro Assunção, Luciano Agostini, and Luis A. da Silva Cruz. "Complexity Scaling for HEVC Using Adaptive Partitioning Structures." In Complexity-Aware High Efficiency Video Coding, 87–124. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25778-5_5.

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Chen, Michael C., and Alan N. Willson. "A Logarithmic-Time Adaptive Block-Matching Algorithm for Estimating Large-Displacement Motion Vectors." In Multimedia Communications and Video Coding, 317–24. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0403-6_39.

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Chen, Lulin, Chang Wen Chen, and Jiebo Lou. "A Cellular Connectionist Architecture for Clustering-Based Adaptive Quantization with Application to Video Coding." In Multimedia Communications and Video Coding, 333–40. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-0403-6_41.

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Ramzan, Naeem, and Ebroul Izquierdo. "Adaptive Joint Source-Channel Coding for Scalable Video." In Encyclopedia of Multimedia, 3–8. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78414-4_5.

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Tang, Chih-Wei. "Motion Perception Based Adaptive Quantization for Video Coding." In Advances in Multimedia Information Processing - PCM 2005, 132–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11581772_12.

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Conference papers on the topic "Adaptive video coding"

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Lin, Chih-Hsuan, Yi-Hsin Chen, and Wen-Hsiao Peng. "Content-Adaptive Motion Rate Adaption For Learned Video Compression." In 2022 Picture Coding Symposium (PCS). IEEE, 2022. http://dx.doi.org/10.1109/pcs56426.2022.10018046.

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Itani, Yusuke, Shunichi Sekiguchi, and Yoshihisa Yamada. "Adaptive direct vector derivation for video coding." In 2010 Picture Coding Symposium (PCS). IEEE, 2010. http://dx.doi.org/10.1109/pcs.2010.5702458.

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Zhao, Jie, Kiran Misra, and Andrew Segall. "Content-adaptive upsampling for scalable video coding." In 2013 Picture Coding Symposium (PCS). IEEE, 2013. http://dx.doi.org/10.1109/pcs.2013.6737762.

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Lim, Wang-Q., Heiko Schwarz, Detlev Marpe, and Thomas Wiegand. "Post Sample Adaptive Offset for Video Coding." In 2019 Picture Coding Symposium (PCS). IEEE, 2019. http://dx.doi.org/10.1109/pcs48520.2019.8954544.

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Leung, Kwong-Keung, Nelson H. C. Yung, and Paul Y. S. Cheung. "Adaptive parallel video coding algorithm." In Photonics West 2001 - Electronic Imaging, edited by Bernd Girod, Charles A. Bouman, and Eckehard G. Steinbach. SPIE, 2000. http://dx.doi.org/10.1117/12.411806.

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Wang, Ren-Jie, Ming-Chen Chien, and Pao-Chi Chang. "Adaptive down-sampling video coding." In IS&T/SPIE Electronic Imaging, edited by Reiner Creutzburg and David Akopian. SPIE, 2010. http://dx.doi.org/10.1117/12.840257.

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Kim, Yong-Kwan, Rin C. Kim, and Sang Uk Lee. "Adaptive 3D subband video coding." In Visual Communications and Image Processing '96, edited by Rashid Ansari and Mark J. T. Smith. SPIE, 1996. http://dx.doi.org/10.1117/12.233200.

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Wang, Ren-Jie, Chih-Wei Huang, and Pao-Chi Chang. "Adaptive coding configuration for multi-resolution video coding." In 2013 IEEE 17th International Symposium on Consumer Electronics (ISCE). IEEE, 2013. http://dx.doi.org/10.1109/isce.2013.6570205.

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Glantz, Alexander, Andreas Krutz, and Thomas Sikora. "Adaptive global motion temporal prediction for video coding." In 2010 Picture Coding Symposium (PCS). IEEE, 2010. http://dx.doi.org/10.1109/pcs.2010.5702463.

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Wang, Yongzhe, Nikolce Stefanoski, Xiangzhong Fang, and Aljoscha Smolic. "Content-adaptive spatial scalability for scalable video coding." In 2010 Picture Coding Symposium (PCS). IEEE, 2010. http://dx.doi.org/10.1109/pcs.2010.5702471.

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Reports on the topic "Adaptive video coding"

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Topiwala, P. T. Rate-Adaptive Video Coding (RAVC). Fort Belvoir, VA: Defense Technical Information Center, May 2008. http://dx.doi.org/10.21236/ada482958.

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