Showing 1 - 20 results of 58 for search 'Formula Super Vee~', query time: 3.83s Refine Results
  1. 1
  2. 2

    Quadratures with super power convergence by Aleksandr A. Belov, Maxim A. Tintul, Valentin S. Khokhlachev

    Published 2023-12-01
    “…The replacement of integration variables is proposed, which dramatically increases the accuracy of the formula of averages. For infinitely smooth integrand functions, the convergence law becomes super power. …”
    Get full text
    Article
  3. 3
  4. 4

    A Study on the Super Resolution Combining Spatial Attention and Channel Attention by Dongwoo Lee, Kyeongseok Jang, Soo Young Cho, Seunghyun Lee, Kwangchul Son

    Published 2023-03-01
    “…The extracted features were expanded through sub-pixel convolution to create super resolution images, and learning was performed through <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>L</mi><mn>1</mn></msub></mrow></semantics></math></inline-formula> loss. …”
    Get full text
    Article
  5. 5

    Area-Specific Convolutional Neural Networks for Single Image Super-Resolution by Honnang Alao, Tae Sung Kim, Kyujoong Lee

    Published 2022-01-01
    “…It consists of high parameter convolutions and low parameter convolutions to process the high-frequency areas and low-frequency areas separately, which efficiently reduces the FLOPs (floating-point operation) while maintaining restoration quality. The settings for reduction are configurable and experimental results show that ASCNN achieves state-of-the-art performance with FLOPs reduction up to 40.1&#x0025; / 37.0&#x0025; / 34.0&#x0025; for <inline-formula> <tex-math notation="LaTeX">$\times 2/\times 3/\times 4$ </tex-math></inline-formula> scale factors.…”
    Get full text
    Article
  6. 6

    Learning Enriched Features for Image Super Resolution by Weiqin Huang, Xiaorui Li, Yikai Gu, Xiaofu Du, Xiancheng Zhu

    Published 2022-01-01
    “…However, most of them do not fully utilize multi-scale feature correspondence in the image SR process, resulting in blurred and artifact detail restoration, especially for SR tasks with larger scaling factors (i.e. <inline-formula> <tex-math notation="LaTeX">$\times 4$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\times 8$ </tex-math></inline-formula>). …”
    Get full text
    Article
  7. 7

    Autoencoder-Inspired Convolutional Network-Based Super-Resolution Method in MRI by Seonyeong Park, H. Michael Gach, Siyong Kim, Suk Jin Lee, Yuichi Motai

    Published 2021-01-01
    “…However, the average computation speed of ACNS was 6, 4, and 35 times faster than SRCNN, FSRCNN, and DRCN, respectively under the computer setup used with the actual average computation time of 0.15 s per <inline-formula> <tex-math notation="LaTeX">$100\times100$ </tex-math></inline-formula> pixels. …”
    Get full text
    Article
  8. 8

    High-Efficiency Super-Resolution FMCW Radar Algorithm Based on FFT Estimation by Bong-seok Kim, Youngseok Jin, Jonghun Lee, Sangdong Kim

    Published 2021-06-01
    “…Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-resolution algorithm depends on the coarsely estimated ranges of targets using the FFT. …”
    Get full text
    Article
  9. 9

    SOFFLFM: Super-resolution optical fluctuation Fourier light-field microscopy by Haixin Huang, Haoyuan Qiu, Hanzhe Wu, Yihong Ji, Heng Li, Bin Yu, Danni Chen, Junle Qu

    Published 2023-05-01
    “…Fourier light-field microscopy (FLFM) uses a microlens array (MLA) to segment the Fourier plane of the microscopic objective lens to generate multiple two-dimensional perspective views, thereby reconstructing the three-dimensional (3D) structure of the sample using 3D deconvolution calculation without scanning. …”
    Get full text
    Article
  10. 10

    Complexity-Reduced Super Resolution for Foveation-Based Driving Head Mounted Displays by Hyoungsik Nam, Hangyeol Kang

    Published 2021-01-01
    “…PSNR and SSIM performances of the proposed SR for the <inline-formula> <tex-math notation="LaTeX">$4\times $ </tex-math></inline-formula> scale are estimated as 31.152 dB and 0.935 for Set5, 26.656 dB and 0.858 for Set14, 27.138 dB and 0.830 for BSD100, and 25.078 dB and 0.836 for Urban100. …”
    Get full text
    Article
  11. 11

    A Sparse Denoising-Based Super-Resolution Method for Scanning Radar Imaging by Qiping Zhang, Yin Zhang, Yongchao Zhang, Yulin Huang, Jianyu Yang

    Published 2021-07-01
    “…This method uses the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>1</mn></msub></semantics></math></inline-formula> norm to represent the sparse prior of the target and solves the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>1</mn></msub></semantics></math></inline-formula> regularization problem to achieve super-resolution imaging under the regularization framework. …”
    Get full text
    Article
  12. 12

    A novel soft start method of super large capacity high voltage motor by Jiaxin Yuan, Chuansheng Wang, Yong Zhu, Baichao Chen

    Published 2019-09-01
    “…The large current generated by starting directly of super large capacity and high voltage induction motor would have a huge impact on the grid as well as the motor itself. …”
    Get full text
    Article
  13. 13

    Microphysical processes of super typhoon Lekima (2019) and their impacts on polarimetric radar remote sensing of precipitation by Y. Gou, Y. Gou, H. Chen, H. Zhu, L. Xue

    Published 2023-02-01
    “…(iii) The twin-parameter radar rainfall estimates based on measured <span class="inline-formula"><i>Z</i><sub>H</sub></span> (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M12" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">H</mi><mi mathvariant="normal">M</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="17pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="150fd6eb2567fa2943cf21893872fc53"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00004.svg" width="17pt" height="17pt" src="acp-23-2439-2023-ie00004.png"/></svg:svg></span></span>) and <span class="inline-formula"><i>Z</i><sub>DR</sub></span> (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M14" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">DR</mi><mi mathvariant="normal">M</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="21pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="4d0a4e7a912a5656995ac6d0a688c5e8"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00005.svg" width="21pt" height="17pt" src="acp-23-2439-2023-ie00005.png"/></svg:svg></span></span>), and their corrected counterparts <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M15" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">H</mi><mi mathvariant="normal">C</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="16pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="7f7f110aeb6a292ec6863cdc170ccc6f"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00006.svg" width="16pt" height="17pt" src="acp-23-2439-2023-ie00006.png"/></svg:svg></span></span> and <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M16" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">DR</mi><mi mathvariant="normal">C</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="21pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="af4a4e5ee9464b435f4bf90421f3bbba"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00007.svg" width="21pt" height="17pt" src="acp-23-2439-2023-ie00007.png"/></svg:svg></span></span>, i.e., <span class="inline-formula"><i>R</i></span>(<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M18" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">H</mi><mi mathvariant="normal">M</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="17pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="77e15ea304c9522c6f92321079f9e5ec"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00008.svg" width="17pt" height="17pt" src="acp-23-2439-2023-ie00008.png"/></svg:svg></span></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M19" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">DR</mi><mi mathvariant="normal">M</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="21pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="919f86b94f71d352e6186282d91b12fa"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00009.svg" width="21pt" height="17pt" src="acp-23-2439-2023-ie00009.png"/></svg:svg></span></span>) and <span class="inline-formula"><i>R</i></span>(<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M21" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">H</mi><mi mathvariant="normal">C</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="16pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="ab6a8397b14785152e190760d17de066"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00010.svg" width="16pt" height="17pt" src="acp-23-2439-2023-ie00010.png"/></svg:svg></span></span>, <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M22" display="inline" overflow="scroll" dspmath="mathml"><mrow><msubsup><mi>Z</mi><mi mathvariant="normal">DR</mi><mi mathvariant="normal">C</mi></msubsup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="21pt" height="17pt" class="svg-formula" dspmath="mathimg" md5hash="fa9dee1500ca6a2b5ccd43fb45b88d15"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-23-2439-2023-ie00011.svg" width="21pt" height="17pt" src="acp-23-2439-2023-ie00011.png"/></svg:svg></span></span>), both tend to overestimate rainfall around the GWS of YDM, mainly ascribed to the unique microphysical process in which the breakup-dominated small-sized drops above transition to the coalescence-dominated large-sized drops falling near the surface. …”
    Get full text
    Article
  14. 14

    Design and Analysis of a Novel 24 GHz Up-Conversion Mixer with Improved Derivative Super-Position Linearizer Technique for 5G Applications by Abrar Siddique, Tahesin Samira Delwar, Prangyadarsini Behera, Manas Ranjan Biswal, Amir Haider, Jee-Youl Ryu

    Published 2021-09-01
    “…The power consumption of the mixer is 4.9 mW at 1.2 V, while the chip area of the designed mixer is 0.4 mm<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mn>2</mn></msup></semantics></math></inline-formula>.…”
    Get full text
    Article
  15. 15

    SR-FEINR: Continuous Remote Sensing Image Super-Resolution Using Feature-Enhanced Implicit Neural Representation by Jinming Luo, Lei Han, Xianjie Gao, Xiuping Liu, Weiming Wang

    Published 2023-03-01
    “…However, for subsequent processing, such as detection and classification, the resolution of the input image may vary greatly for different methods. In this paper, we propose a method for continuous remote sensing image super-resolution using feature-enhanced implicit neural representation (SR-FEINR). …”
    Get full text
    Article
  16. 16
  17. 17

    Effects of the super-powerful tropospheric western Pacific phenomenon of September–October 2018 on the ionosphere over China: results from oblique sounding by L. F. Chernogor, L. F. Chernogor, L. F. Chernogor, K. P. Garmash, Q. Guo, V. T. Rozumenko, Y. Zheng

    Published 2023-04-01
    “…The periods and amplitudes of quasi-sinusoidal variations in the Doppler shift, which have been determined for all propagation paths, may be used to estimate the amplitudes, <span class="inline-formula"><i>δ</i><sub>Na</sub></span>, of quasi-sinusoidal variations in the electron density. …”
    Get full text
    Article
  18. 18

    FORMULASI TABLET EKSTRAK SAMBILOTO (Andrographis paniculata Nees) by , AWAL PRICHATIN KUSUMA DEWI, , Prof. Dr. Sri Sulihtyowati Soebagyo, Apt.

    Published 2011
    “…Based on equations, contour plots and super imposed of the contour plots using Design Expert7.0.0, the optimum formula of sambilotoâ��s extract tablet was obtained with 78,1 â�� 87,55% Avicel PH 102 and 7,19 â�� 7,82% Explotab of the extract weight producing tablet with disintegration time of 4,02 â�� 10,03 minutes and andrographolide dissolution (Q45) of 75,30 â�� 82,44%.…”
    Thesis
  19. 19

    Application and development of fluorescence probes in MINFLUX nanoscopy (invited paper) by Jing Wang, Zhen Zhang, Hongyu Shen, Qi Wu, Min Gu

    Published 2023-01-01
    “…This paper mainly focuses on recent applications and developments of fluorescence probes and the relevant labeling strategy for MINFLUX microscopy. Moreover, we discuss the deficiencies that need to be addressed in the future and a plan for the possible progression of MINFLUX to help investigators who have been involved in or are just starting in the field of super-resolution imaging microscopy with theoretical support.…”
    Get full text
    Article
  20. 20