Search Results - "Duanmu, Chunjiang"

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  1. 1

    The Image Super-Resolution Algorithm Based on the Dense Space Attention Network (July 2020) by Duanmu, Chunjiang, Zhu, Junjie

    Published in IEEE access (01-01-2020)
    “…The deep learning technique has been recently used in the image super-resolution. When the deep learning network is too deep, it is difficult to train this…”
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    Journal Article
  2. 2

    Reduction of the PAPR in OFDM Systems by Intelligently Applying Both PTS and SLM Algorithms by Duanmu, Chunjiang, Chen, Hongtao

    Published in Wireless personal communications (2014)
    “…The orthogonal frequency division multiplex (OFDM) technique, which is used in the 4G communications, has a shortcoming of having a high peak to average power…”
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    Journal Article
  3. 3

    Multi-channel satellite cloud image fusion in the tetrolet transform domain by Zhang, Chang-Jiang, Chen, Yuan, Duanmu, Chunjiang, Feng, Hua-Jun

    Published in International journal of remote sensing (17-12-2014)
    “…A novel multi-channel satellite cloud image fusion algorithm constructed in the tetrolet transform domain is proposed. Tetrolet is successfully applied in…”
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    Journal Article
  4. 4

    Simplified Successive Cancellation Decoding of Polar Codes With Medium-Dimensional Binary Kernels by Huang, Zhiliang, Zhang, Shiyi, Zhang, Feiyan, Duanmu, Chunjiang, Zhong, Farong, Chen, Ming

    Published in IEEE access (01-01-2018)
    “…A method is proposed, called l-formula, to design efficient successive cancellation (SC) decoding of polar codes with medium-dimensional binary kernels…”
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    Journal Article
  5. 5

    An Improvement of Modified Successive-Cancellation Decoder for Polar Codes by Huang, Zhiliang, Diao, Chunjuan, Dai, Jianxin, Duanmu, Chunjiang, Wu, Xia, Chen, Ming

    Published in IEEE communications letters (01-12-2013)
    “…An improvement is introduced of the modified successive-cancellation (MSC) decoding for polar codes, in which local decoders at rate-other nodes are…”
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    Journal Article
  6. 6

    Fast Block Motion Estimation With 8-Bit Partial Sums Using SIMD Architectures by Duanmu, C.J., Ahmad, M.O., Swamy, M.N.S.

    “…In order to take advantage of the byte-type data parallelism in the existing single-instruction multiple-data (SIMD) technique, this paper introduces the…”
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    Journal Article
  7. 7

    A new super-resolution algorithm by interpolation in homogeneous areas by Chunjiang Duanmu, Di Zhao

    “…Single image super-resolution technique has been used in wide applications to enlarge the resolution of a image. In this paper, a new single image…”
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    Conference Proceeding
  8. 8

    Image denoising by using PDE and GCV in tetrolet transform domain by Zhang, Changjiang, Chen, Yuan, Duanmu, Chunjiang, Yang, Yinhuan

    “…The proposed algorithm, which uses partial differential equations (PDE) and generalized cross validation (GCV) theory in the tetrolet transform domain, is used…”
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    Journal Article
  9. 9

    A new power saving algorithm for the transmission of compressed medical video stream by Chunjiang Duanmu, Hongtao Chen

    “…In the compressed medical video stream, different kinds of bits have different influences on the quality of the reconstructed video. Traditional unequal error…”
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    Conference Proceeding
  10. 10

    Adaptive typhoon cloud image enhancement using genetic algorithm and non-linear gain operation in undecimated wavelet domain by Zhang, Changjiang, Wang, Xiaodong, Duanmu, Chunjiang

    “…By combining discrete undecimated wavelet transform (UWT) with genetic algorithm (GA) an efficient enhancement algorithm for typhoon cloud image is proposed…”
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    Journal Article
  11. 11

    A timing synchronization method for MIMO-OFDM systems by Duanmu Chunjiang, Huang Feng

    “…This paper proposes a time and frequency synchronizaton algorithm for MIMO-OFDM systems. This algorithm designed a training sequence that based on CAZAC…”
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    Conference Proceeding
  12. 12

    Leveraging CNN-CPU Scheduling for Enhanced Resource Management in Storage Edge Network Frameworks by Alwahedi, Mazen, Duanmu, Chunjiang

    “…Because the landscape of data processing created is likely to rise considerably in the next years due to the proliferation of devices that require data…”
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    Conference Proceeding
  13. 13

    Edge-constrained Residual Semantic Attention for Image Restoration by Lu, Qinyi, Duanmu, Chunjiang

    “…Currently, image restoration models have achieved significant advancements. However, in cases where the missing regions are too large, it often leads to…”
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    Conference Proceeding
  14. 14

    Residual Attention Mechanism-Based MRI Super-Resolution by Sun, Hao, Duanmu, Chunjiang

    “…MRI (Magnetic Resonance Imaging) super-resolution technology is a crucial research direction in the field of medical image processing. This paper aims to…”
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    Conference Proceeding
  15. 15

    Fast mode decision algorithm in H.264/AVC base on statistical feature by Donghui Zhou, Chunjiang Duanmu

    “…H.264/AVC uses the Rate Distortion Optimization (RDO) technique to select intra and inter prediction modes in order to achieve coding efficiency, but the huge…”
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    Conference Proceeding
  16. 16

    Retinal Blood Vessel Segmentation with Attentive Feature Fusion by Djamal, Hassan Ibrahim, Duanmu, Chunjiang

    “…This study investigates the utilization of sophisticated deep learning techniques, specifically, the integration of UNet and ResNet models with attention…”
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    Conference Proceeding
  17. 17

    Large Kernel Frequency-enhanced Network for Efficient Single Image Super-Resolution by Chen, Jiadi, Duanmu, Chunjiang, Long, Huanhuan

    “…In recent years, there has been significant progress in efficient and lightweight image super-resolution, due in part to the design of several powerful and…”
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    Conference Proceeding
  18. 18

    Facial feature localization based on an improved active shape model by Zheng, Zhonglong, Jiong, Jia, Chunjiang, Duanmu, Liu, XinHong, Yang, Jie

    Published in Information sciences (01-05-2008)
    “…The original active shape model (ASM) has already been applied to the areas such as image segmentation, feature points localization, and contour extraction…”
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    Journal Article
  19. 19

    The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report by Ren, Bin, Mehta, Nancy, Timofte, Radu, Yu, Hongyuan, Wan, Cheng, Han, Bingnan, Wu, Zhuoyuan, Zou, Yajun, Li, Jizhe, Fan, Chao, Yin, Xuanwu, Zuo, Kunlong, Liao, Bohao, Xia, Peizhe, Peng, Long, Du, Zhibo, Di, Xin, Wang, Yang, Guo, Jiaming, Xu, Songcen, Cao, Yang, Zha, Zhengjun, Wang, Yan, Liu, Yi, Wang, Qing, Zhang, Liou, Zhao, Shijie, Sun, Long, Pan, Jinshan, Dong, Jiangxin, Tang, Jinhui, Liu, Xin, Wang, Qian, Zhou, Menghan, Yan, Yiqiang, Chan, Wensong, Zhou, Dong, Wang, Li, Tian, Lu, Emad, Barsoum, Zhou, Yunshuai, Zhang, Yun, Li, Wei, Zhao, Suiyi, Wang, Bo, Luo, Yan, Wei, Yanyan, Li, Yawei, Guan, Jinhan, Hu, Dehua, Yu, Jiawei, Sun, Tao, Lan, Long, Xu, Kele, Lin, Xin, Yue, Jingtong, Yang, Lehan, Du, Shiyi, Qi, Lu, Ren, Chao, Han, Zeyu, Chen, Chaolin, Li, Haobo, Zheng, Mingjun, Song, Lianhong, Yan, Xingzhuo, Fu, Minghan, Zhang, Jingyi, Zhu, Qi, Xu, Xiaogang, Guo, Dan, Guo, Chunle, Chen, Jiadi, Duanmu, Chunjiang, Liu, Jie, Jia, Weilin, Zhang, Wenlong, Mao, Yanyu, Guo, Ruilong, Zhang, Nihao, Wang, Qian, Pandey, Manoj, Chernozhukov, Maksym, Le, Giang, Cheng, Shuli, Wang, Hongyuan, Wei, Ziyan, Tang, Qingting, Wang, Liejun, Li, Yongming, Guo, Yanhui, Khatami-Rizi, Akram, Hsu, Chih-Chung, Lee, Chia-Ming, Akalwadi, Nikhil, Malagi, Sampada, Yashaswini, Palani, Desai, Chaitra, Tabib, Ramesh Ashok, Mudenagudi, Uma

    “…This paper provides a comprehensive review of the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions and their outcomes…”
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    Conference Proceeding
  20. 20

    A Three Dimension Super-Resolution Algorithm through Neighbor Embedding Based on Weighted Coefficient Values for Internet of Things by Duanmu, Chunjiang, Zhao, Di, Jiang, Dingde, Song, Houbing, Xiong, Jiping

    “…In the applications of the internet of things (IOT), the nodes in the network usually has power limits and storage space limits. Thus, the images over the IOT…”
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    Conference Proceeding