Relevant bibliographies by topics / Data compression (Telecommunication)

Contents

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

Academic literature on the topic 'Data compression (Telecommunication)'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Data compression (Telecommunication)"

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Shibaikin, Sergei, Andrei Abbakumov, Vladimir Nikulin, and Maria S. Sokolova. "TELECOMMUNICATIONS CONVERTER FOR VISUALIZATION AND NAVIGATION SYSTEM IN LOW-INVASIVE MEDICAL MANIPULATIONS." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2021, no. 2 (April 30, 2021): 66–74. http://dx.doi.org/10.24143/2072-9502-2021-2-66-74.

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The article highlights the progress of information and telecommunication technologies as a basis for studying modern medical diagnostics, where digital technologies are widely used. Digital medical images can be easily analyzed, stored, and transmitted over telecommunica-tions channels. Most manufacturers support the DICOM medical standard which contains complete, but in many cases redundant, information. There is considered the process of developing a cross-platform telecommunications converter of medical images for the system of visualization and navigation in low-invasive medical manipulations. The popular medical image format DICOM is considered in detail. An algorithm for converting data from the DICOM format into standard graphic files has been developed. The results of the converter operation are analyzed in the case of such characteristics as compression, signal-to-noise level and compression rate.
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Riznyk, Volodymyr. "Optimum Vector Information Technologies Based on the Multidimensional Combinatorial Configurations." International Journal of Computational and Applied Mathematics & Computer Science 3 (November 6, 2023): 104–12. http://dx.doi.org/10.37394/232028.2023.3.12.

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Paper devoiced to optimum vector information technologies based on the multi-dimensional combinatorial configurations, such as Ideal Ring Bundles (IRBs). One-dimensional IRBs are ring ordered positive integers that form finite set of integers from 1 to S using both these numbers and all its consecutive terms. Two- and multi-dimensional IRBs make available to configure intelligent information and telecommunication systems providing generate the maximum number of distinct vector sums of consecutive terms in the combinatorial configuration. Applications profiting from optimum vector information technologies based on the multi-dimensional combinatorial theory provide for example data mining technologies and big vector data processing, data analysis and system security, signal compression and reconstruction, vector computing and telecommunications, and other branches of sciences and advanced information technologies.
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Korchynskyj, V. M., and I. O. Kozar. "APPLICATION OF SIGNAL COMPRESSION TO CONTROL DATA RATES IN ADDITIVE NOISE TELECOMMUNICATION CHANNELS." Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Sciences, no. 4 (2023): 1–4. http://dx.doi.org/10.32782/2663-5941/2023.4/01.

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Zebin, Tahmina, Ekramul Farook, Syeda Zinath Aman, and Shahida Rafique. "LSPIHT Algorithm for ECG Data Compression and Transmission for Telemedicine Applications." Dhaka University Journal of Science 60, no. 1 (April 14, 2012): 31–36. http://dx.doi.org/10.3329/dujs.v60i1.10332.

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Medical image analysis and data compression are rapidly evolving fields with growing applications in healthcare services e.g. teleradiology, teleconsultation, e-health, telemedicine and statistical analysis of medical data. In this paper, a Layered Set Partitioning in Hierarchical Trees (LSPIHT) algorithm for medical data compression and transmission is presented. In the LSPIHT, the encoded bit streams are divided into a number of layers for transmission and reconstruction. Starting from the base layer, by accumulating bit streams up to different enhancement layers, medical data can be reconstructed with various signal-to-noise ratios (SNRs) and resolutions. Receivers with distinct specifications can then share the same source encoder to reduce the complexity of telecommunication networks for telemedicine applications. The algorithm is compared with other algorithms for encoding ECG data, and analysis shows that the LSPIHT attains better rate-distortion performance and low network complexity than other encoding techniques.DOI: http://dx.doi.org/10.3329/dujs.v60i1.10332 Dhaka Univ. J. Sci. 60(1): 31-36, 2012 (January)
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Rahman, Md Atiqur, and Mohamed Hamada. "Lossless text compression using GPT-2 language model and Huffman coding." SHS Web of Conferences 102 (2021): 04013. http://dx.doi.org/10.1051/shsconf/202110204013.

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Modern daily life activities produced lots of information for the advancement of telecommunication. It is a challenging issue to store them on a digital device or transmit it over the Internet, leading to the necessity for data compression. Thus, research on data compression to solve the issue has become a topic of great interest to researchers. Moreover, the size of compressed data is generally smaller than its original. As a result, data compression saves storage and increases transmission speed. In this article, we propose a text compression technique using GPT-2 language model and Huffman coding. In this proposed method, Burrows-Wheeler transform and a list of keys are used to reduce the original text file’s length. Finally, we apply GPT-2 language mode and then Huffman coding for encoding. This proposed method is compared with the state-of-the-art techniques used for text compression. Finally, we show that the proposed method demonstrates a gain in compression ratio compared to the other state-of-the-art methods.
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Cahya Dewi, Dewa Ayu Indah, and I. Made Oka Widyantara. "Usage analysis of SVD, DWT and JPEG compression methods for image compression." Jurnal Ilmu Komputer 14, no. 2 (September 30, 2021): 99. http://dx.doi.org/10.24843/jik.2021.v14.i02.p04.

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Through image compression, can save bandwidth usage on telecommunication networks, accelerate image file sending time and can save memory in image file storage. Technique to reduce image size through compression techniques is needed. Image compression is one of the image processing techniques performed on digital images with the aim of reducing the redundancy of the data contained in the image so that it can be stored or transmitted efficiently. This research analyzed the results of image compression and measure the error level of the image compression results. The analysis to be carried out is in the form of an analysis of JPEG compression techniques with various types of images. The method of measuring the compression results uses the MSE and PSNR methods. Meanwhile, to determine the percentage level of compression using the compression ratio calculation. The average ratio for JPEG compression was 0.08605, the compression rate was 91.39%. The average compression ratio for the DWT method was 0.133090833, the compression rate was 86.69%. The average compression ratio of the SVD method was 0.101938833 and the compression rate was 89.80%.
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Rahman, Md Atiqur, Mohamed Hamada, and Jungpil Shin. "The Impact of State-of-the-Art Techniques for Lossless Still Image Compression." Electronics 10, no. 3 (February 2, 2021): 360. http://dx.doi.org/10.3390/electronics10030360.

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A great deal of information is produced daily, due to advances in telecommunication, and the issue of storing it on digital devices or transmitting it over the Internet is challenging. Data compression is essential in managing this information well. Therefore, research on data compression has become a topic of great interest to researchers, and the number of applications in this area is increasing. Over the last few decades, international organisations have developed many strategies for data compression, and there is no specific algorithm that works well on all types of data. The compression ratio, as well as encoding and decoding times, are mainly used to evaluate an algorithm for lossless image compression. However, although the compression ratio is more significant for some applications, others may require higher encoding or decoding speeds or both; alternatively, all three parameters may be equally important. The main aim of this article is to analyse the most advanced lossless image compression algorithms from each point of view, and evaluate the strength of each algorithm for each kind of image. We develop a technique regarding how to evaluate an image compression algorithm that is based on more than one parameter. The findings that are presented in this paper may be helpful to new researchers and to users in this area.
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Gertsiy, O. "COMPARATIVE ANALYSIS OF COMPACT METHODS REPRESENTATIONS OF GRAPHIC INFORMATION." Collection of scientific works of the State University of Infrastructure and Technologies series "Transport Systems and Technologies" 1, no. 37 (June 29, 2021): 130–43. http://dx.doi.org/10.32703/2617-9040-2021-37-13.

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The main characteristics of graphic information compression methods with losses and without losses (RLE, LZW, Huffman's method, DEFLATE, JBIG, JPEG, JPEG 2000, Lossless JPEG, fractal and Wawelet) are analyzed in the article. Effective transmission and storage of images in railway communication systems is an important task now. Because large images require large storage resources. This task has become very important in recent years, as the problems of information transmission by telecommunication channels of the transport infrastructure have become urgent. There is also a great need for video conferencing, where the task is to effectively compress video data - because the greater the amount of data, the greater the cost of transmitting information, respectively. Therefore, the use of image compression methods that reduce the file size is the solution to this task. The study highlights the advantages and disadvantages of compression methods. The comparative analysis the basic possibilities of compression methods of graphic information is carried out. The relevance lies in the efficient transfer and storage of graphical information, as big data requires large resources for storage. The practical significance lies in solving the problem of effectively reducing the data size by applying known compression methods.
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Graschew, Georgi, Stefan Rakowsky, Panagiota Balanou, and Peter M. Schlag. "Interactive telemedicine in the operating theatre of the future." Journal of Telemedicine and Telecare 6, no. 2_suppl (August 2000): 20–24. http://dx.doi.org/10.1258/1357633001935824.

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An experimental stereoscopic system has been established in the Robert-Rössle-Klinik, including four operating theatres and the surgical research unit OP 2000. The system allows local three-dimensional image acquisition, local stereoscopic video display, in-house stereoscopic video transmission and stereoscopic links to external partners. The goal is to make high-quality patient data available in a medical centre or over a collaborative network of medical experts. In future the requirements of teleconsultation in terms of image quality and bandwidth will be heterogeneous. A sophisticated medical telecommunication system for second opinions is needed that can take advantage of intelligent compression approaches (e.g. wavelet compression) to archive, to search for image content and to transmit medical data such as images.
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Png, M. A., G. J. L. Kaw, K. P. Tan, B. H. Koh, L. Ang, and J. Filut. "Remote consultation for computerized tomography and magnetic resonance studies by means of teleradiology—experience at the Singapore General Hospital." Journal of Telemedicine and Telecare 3, no. 1_suppl (June 1997): 54–55. http://dx.doi.org/10.1258/1357633971930373.

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A teleradiology link was established between Singapore General Hospital in Singapore and Stanford University in California, USA. Over eight months, a total of 28 cases (involving 27 magnetic resonance investigations and three computerized tomography scans) were transmitted by ISDN to California. Our initial experience with teleradiology for remote consultation was encouraging, although the data transmission cost was higher than we anticipated. However, costs could be reduced by using data compression. Long-distance telecommunication charges continue to fall, so intercontinental teleradiology of this type may be financially viable in future.
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Dissertations / Theses on the topic "Data compression (Telecommunication)"

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Walker, Wendy Tolle 1959. "Video data compression for telescience." Thesis, The University of Arizona, 1988. http://hdl.handle.net/10150/276830.

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This paper recommends techniques to use for data compression of video data used to point a telescope and from a camera observing a robot, for transmission from the proposed U.S. Space Station to Earth. The mathematical basis of data compression is presented, followed by a general review of data compression techniques. A technique that has wide-spread use in data compression of videoconferencing images is recommended for the robot observation data. Bit rates of 60 to 400 kbits/sec can be achieved. Several techniques are modelled to find a best technique for the telescope data. Actual starfield images are used for the evaluation. The best technique is chosen on the basis of which model provides the most compression while preserving the important information in the images. Compression from 8 bits per pel to 0.015 bits per pel is achieved.
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Aydinoğlu, Behçet Halûk. "Stereo image compression." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/15447.

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Chaulklin, Douglas Gary. "Evaluation of ANSI compression in a bulk data file transfer system." Master's thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-01202010-020213/.

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Chen, Mo. "Data compression for inference tasks in wireless sensor networks." Diss., Online access via UMI:, 2006.

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Thesis (Ph. D.)--State University of New York at Binghamton, Department of Electrical Engineering, Thomas J. Watson School of Engineering and Applied Science, 2006.
Includes bibliographical references.
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Goodenow, Daniel P. "A reference guide to JPEG compression /." Online version of thesis, 1993. http://hdl.handle.net/1850/11714.

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Jones, Greg 1963-2017. "RADIX 95n: Binary-to-Text Data Conversion." Thesis, University of North Texas, 1991. https://digital.library.unt.edu/ark:/67531/metadc500582/.

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This paper presents Radix 95n, a binary to text data conversion algorithm. Radix 95n (base 95) is a variable length encoding scheme that offers slightly better efficiency than is available with conventional fixed length encoding procedures. Radix 95n advances previous techniques by allowing a greater pool of 7-bit combinations to be made available for 8-bit data translation. Since 8-bit data (i.e. binary files) can prove to be difficult to transfer over 7-bit networks, the Radix 95n conversion technique provides a way to convert data such as compiled programs or graphic images to printable ASCII characters and allows for their transfer over 7-bit networks.
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Srinivas, Bindignavile S. "Progressive image and video transmission with error concealment on burst error channels and lossy packet networks /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/6015.

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Subramaniam, Suresh. "All-optical networks with sparse wavelength conversion /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/6032.

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Goldschneider, Jill R. "Lossy compression of scientific data via wavelets and vector quantization /." Thesis, Connect to this title online; UW restricted, 1997. http://hdl.handle.net/1773/5881.

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Smith, Craig M. "Efficient software implementation of the JBIG compression standard /." Online version of thesis, 1993. http://hdl.handle.net/1850/11713.

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Books on the topic "Data compression (Telecommunication)"

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Williams, Ross N. Adaptive Data Compression. Boston: Kluwer Academic Publishers, 1991.

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Sayood, Khalid. Introduction to data compression. 3rd ed. Amsterdam: Elsevier, 2006.

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Sayood, Khalid. Introduction to data compression. San Francisco, Calif: Morgan Kaufmann Publishers, 1996.

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Huang, Bormin. Satellite data compression. New York, NY: Springer Science+Business Media, LLC, 2011.

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Ramamohan, Rao K., and Yip P. C, eds. The Transform and Data Compression Handbook. Boca Raton, Fla: CRC Press, 2009.

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United States. National Aeronautics and Space Administration., ed. Data compression using adaptive transform coding. [Washington, DC: National Aeronautics and Space Administration, 1988.

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United States. National Telecommunications and Information Administration., ed. Image data compression overview: Issues and partial solutions. [Boulder, CO]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1989.

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Nesenbergs, M. Image data compression overview: Issues and partial solutions. [Boulder, CO]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1989.

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Bizon, Thomas P. Real-time transmission of digital video using variable-lengthbcoding. [Washington, DC: National Aeronautics and Space Administration, 1993.

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Bizon, Thomas P. Real-time transmission of digital video using variable-lengthbcoding. [Washington, DC: National Aeronautics and Space Administration, 1993.

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Book chapters on the topic "Data compression (Telecommunication)"

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Dorausch, Edgar M. G., Moritz Herzog, Cornelius Kühnöl, Daniel Swist, Tönnis Trittler, Julian Kober, and Gerhard Fettweis. "Evanescent Wave Filtering for Ultrasound RF-Data Compression." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 33–44. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60665-6_3.

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Bowden, David, and Diarmuid Grimes. "Intelligent Image Compression Using Traffic Scene Analysis." In Communications in Computer and Information Science, 332–43. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26438-2_26.

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AbstractThe quantity of images generated at the edge of the Cloud is growing year-on-year, which puts an increasing strain on existing telecommunications infrastructure. There is also an associated increased cost for transmission bandwidth and storage of video images in the Cloud. In our modern society we tend to accumulate data, and are reluctant to throw it away, without asking “what is the value of this data?” and “do we need it?”. One of the major sources of video streams are the increasing number of traffic cameras, used to maintain the efficient flow of vehicles on our roads. In this work we focus on images taken from road traffic cameras, and show how their transmission bandwidth and storage requirements can be reduced. By analysing video feeds on a simulated edge device, we have shown that it is possible to extract objects of interest from the image, and discard or dramatically reduce irrelevant information in the content. Our technique also generates associated metadata, in the form of JSON-LD, which annotates the original image and maintains its semantic fidelity and provenance after compression. Our technique is compatible with conventional compression techniques, and thus the potential bandwidth savings would be incremental. We present the potential savings that can be made in the transmission and storage of unstructured data, as well as some of the challenges still to be overcome.
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Cuzzocrea, Alfredo. "Compressing Big OLAP Data Cubes in Big Data Analytics Systems: New Paradigms, a Reference Architecture, and Future Research Perspectives." In E-Business and Telecommunications, 156–75. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45137-9_7.

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Sun, Shan, Zhaoxia Yin, Jin Tang, and Bin Luo. "Improved Reversible Data Hiding Scheme Based on AMBTC Compression Technique." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 111–18. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60753-5_12.

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Lei, Tao. "Fast Anti-noise Compression Storage Algorithm for Big Data Video Images." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 355–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36405-2_35.

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Tang, Xiaolan, Hua Xie, Wenlong Chen, and Jianwei Niu. "Energy-Efficient Data Collection Using Lossless Compression for Industrial Wireless Sensor Networks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 14–27. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74176-5_2.

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Liu, Xu, and Yanfeng Wu. "An Efficient Compression Coding Method for Multimedia Video Data Based on CNN." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 123–36. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28787-9_10.

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Ma, Ji-shun, Bin Zhao, and Hao Zhang. "Encryption and Compression Storage Method of Educational Resources Based on Complex Network and Big Data Analysis." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 77–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63955-6_7.

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Li, Ang. "Analysis of Surface Compressive Strength of Optical Fiber Composites Under Low Velocity Impact Damage Based on Big Data." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 419–28. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36402-1_45.

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Kester, Quist-Aphetsi. "A Hybrid Lossy Compression Using 2-D Discrete Cosine Transform and Visual Cryptographic Technique for Security of Multimedia Image Data Communications in Internet of Things." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 292–303. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66742-3_28.

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Conference papers on the topic "Data compression (Telecommunication)"

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Stojkoska, Biljana Risteska, and Zoran Nikolovski. "Data compression for energy efficient IoT solutions." In 2017 25th Telecommunication Forum (TELFOR). IEEE, 2017. http://dx.doi.org/10.1109/telfor.2017.8249368.

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Jackson and Szasz. "The Use Of Data Compression In Telecommunication Of Nuclear Medicine Images." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.594796.

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Chawla, Saket, and B. S. Manoj. "Dynamic data compression in wireless networks." In 2011 IEEE 5th International Conference on Advanced Networks and Telecommunication Systems (ANTS). IEEE, 2011. http://dx.doi.org/10.1109/ants.2011.6163657.

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Kozhin, Aleksey S., and Alexander V. Surchenko. "Design of Data Compression Mechanism in Cache Memory of Elbrus Processors." In 2020 International Conference Engineering and Telecommunication (En&T). IEEE, 2020. http://dx.doi.org/10.1109/ent50437.2020.9431291.

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Polyakov, V. B., N. A. Ignatova, and A. A. Sentsov. "Multi-Criteria Selection of the Radar Data Compression Method." In 2021 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF). IEEE, 2021. http://dx.doi.org/10.1109/weconf51603.2021.9470755.

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Li, Biwei, Yu Guo, Zhenqiang Mi, Yang Yang, and Mohammad S. Obaidat. "A Novel Data Compression Technique Incorporated with Computer Offloading in RGB-D SLAM." In 2019 International Conference on Computer, Information and Telecommunication Systems (CITS). IEEE, 2019. http://dx.doi.org/10.1109/cits.2019.8862000.

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Rani, Kajal, and Raj Kumar Sagar. "Enhanced data storage security in cloud environment using encryption, compression and splitting technique." In 2017 2nd International Conference on Telecommunication and Networks (TEL-NET). IEEE, 2017. http://dx.doi.org/10.1109/tel-net.2017.8343557.

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Jia, Yichen, Zili Shao, and Feng Chen. "SlimCache: Exploiting Data Compression Opportunities in Flash-Based Key-Value Caching." In 2018 IEEE 26th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS). IEEE, 2018. http://dx.doi.org/10.1109/mascots.2018.00029.

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Serhii, Ushakov, and Kurdecha Vasyl. "Optimizing Data Transmission in IoT Networks through Enhanced Compression and Edge Computing Techniques." In 2023 IEEE International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo). IEEE, 2023. http://dx.doi.org/10.1109/ukrmico61577.2023.10380347.

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Corda, Roberto. "Digital Holography Data Compression." In 2018 26th Telecommunications Forum (TELFOR). IEEE, 2018. http://dx.doi.org/10.1109/telfor.2018.8611964.

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