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  • Open Access


    Instance Retrieval Using Region of Interest Based CNN Features

    Jingcheng Chen1, Zhili Zhou1,2,*, Zhaoqing Pan1, Ching-nung Yang3

    Journal of New Media, Vol.1, No.2, pp. 87-99, 2019, DOI:10.32604/jnm.2019.06582

    Abstract Recently, image representations derived by convolutional neural networks (CNN) have achieved promising performance for instance retrieval, and they outperform the traditional hand-crafted image features. However, most of existing CNN-based features are proposed to describe the entire images, and thus they are less robust to background clutter. This paper proposes a region of interest (RoI)-based deep convolutional representation for instance retrieval. It first detects the region of interests (RoIs) from an image, and then extracts a set of RoI-based CNN features from the fully-connected layer of CNN. The proposed RoI-based CNN feature describes the patterns of the detected RoIs, so that… More >

  • Open Access


    Low-Dose CT Image Denoising Based on Improved WGAN-gp

    Xiaoli Li1,*, Chao Ye1, Yujia Yan2, Zhenlong Du1

    Journal of New Media, Vol.1, No.2, pp. 75-85, 2019, DOI:10.32604/jnm.2019.06259

    Abstract In order to improve the quality of low-dose computational tomography (CT) images, the paper proposes an improved image denoising approach based on WGAN-gp with Wasserstein distance. For improving the training and the convergence efficiency, the given method introduces the gradient penalty term to WGAN network. The novel perceptual loss is introduced to make the texture information of the low-dose images sensitive to the diagnostician eye. The experimental results show that compared with the state-of-art methods, the time complexity is reduced, and the visual quality of low-dose CT images is significantly improved. More >

  • Open Access


    Review on Video Object Tracking Based on Deep Learning

    Fangming Bi1,2, Xin Ma1,2, Wei Chen1,2,*, Weidong Fang3, Huayi Chen1,2, Jingru Li1,2, Biruk Assefa1,4

    Journal of New Media, Vol.1, No.2, pp. 63-74, 2019, DOI:10.32604/jnm.2019.06253

    Abstract Video object tracking is an important research topic of computer vision, which finds a wide range of applications in video surveillance, robotics, human-computer interaction and so on. Although many moving object tracking algorithms have been proposed, there are still many difficulties in the actual tracking process, such as illumination change, occlusion, motion blurring, scale change, self-change and so on. Therefore, the development of object tracking technology is still challenging. The emergence of deep learning theory and method provides a new opportunity for the research of object tracking, and it is also the main theoretical framework for the research of moving… More >

  • Open Access


    Multi-Label Chinese Comments Categorization: Comparison of Multi-Label Learning Algorithms

    Jiahui He1, Chaozhi Wang1, Hongyu Wu1, Leiming Yan1,*, Christian Lu2

    Journal of New Media, Vol.1, No.2, pp. 51-61, 2019, DOI:10.32604/jnm.2019.06238

    Abstract Multi-label text categorization refers to the problem of categorizing text through a multi-label learning algorithm. Text classification for Asian languages such as Chinese is different from work for other languages such as English which use spaces to separate words. Before classifying text, it is necessary to perform a word segmentation operation to convert a continuous language into a list of separate words and then convert it into a vector of a certain dimension. Generally, multi-label learning algorithms can be divided into two categories, problem transformation methods and adapted algorithms. This work will use customer's comments about some hotels as a… More >

  • Open Access


    LDPC Code’s Decoding Algorithms for Wireless Sensor Network: a Brief Review

    Weidong Fang1, Wuxiong Zhang1,2, Lianhai Shan1,*, Biruk Assefa3, Wei Chen4

    Journal of New Media, Vol.1, No.1, pp. 45-50, 2019, DOI:10.32604/jnm.2019.05786

    Abstract As an effective error correction technology, the Low Density Parity Check Code (LDPC) has been researched and applied by many scholars. Meanwhile, LDPC codes have some prominent performances, which involves close to the Shannon limit, achieving a higher bit rate and a fast decoding. However, whether these excellent characteristics are suitable for the resource-constrained Wireless Sensor Network (WSN), it seems to be seldom concerned. In this article, we review the LDPC code’s structure brief.ly, and them classify and summarize the LDPC codes’ construction and decoding algorithms, finally, analyze the applications of LDPC code for WSN. We believe that our contributions… More >

  • Open Access


    Overview of Digital Image Restoration

    Wei Chen1, 2, Tingzhu Sun1, 2, Fangming Bi1, 2, *, Tongfeng Sun1, 2, Chaogang Tang1, 2, Biruk Assefa1, 3

    Journal of New Media, Vol.1, No.1, pp. 35-44, 2019, DOI:10.32604/jnm.2019.05803

    Abstract Image restoration is an image processing technology with great practical value in the field of computer vision. It is a computer technology that estimates the image information of the damaged area according to the residual image information of the damaged image and carries out automatic repair. This article firstly classify and summarize image restoration algorithms, and describe recent advances in the research respectively from three aspects including image restoration based on partial differential equation, based on the texture of image restoration and based on deep learning, then make the brief analysis of digital image restoration of subjective and objective evaluation… More >

  • Open Access


    Preservation Mechanism of Network Electronic Records Based on Broadcast-Storage Network in Urban Construction

    Fujian Zhu1,2, Yongjun Ren1,2,*, Qirun Wang3,4, Jinyue Xia5

    Journal of New Media, Vol.1, No.1, pp. 27-34, 2019, DOI:10.32604/jnm.2019.05920

    Abstract With the wide application of information technology in urban infrastructure, urban construction has entered the stage of smart city, forming a large number of network electronic records. These electronic records play a vital role in the maintenance of urban infrastructure. However, how to preserve the network electronic records in the field of urban construction is still lack of a comprehensive and serious study. Aiming at this problem, the paper proposes to use the technology of broadcast-storage network to preserve the network electronic records for a long time and gives the concrete preservation process. More >

  • Open Access


    A Survey on Digital Image Copy-Move Forgery Localization Using Passive Techniques

    Weijin Tan1,*, Yunqing Wu1, Peng Wu1, Beijing Chen1,2

    Journal of New Media, Vol.1, No.1, pp. 11-25, 2019, DOI:10.32604/jnm.2019.06219

    Abstract Digital images can be tampered easily with simple image editing software tools. Therefore, image forensic investigation on the authenticity of digital images’ content is increasingly important. Copy-move is one of the most common types of image forgeries. Thus, an overview of the traditional and the recent copy-move forgery localization methods using passive techniques is presented in this paper. These methods are classified into three types: block-based methods, keypoint-based methods, and deep learning-based methods. In addition, the strengths and weaknesses of these methods are compared and analyzed in robustness and computational cost. Finally, further research directions are discussed. More >

  • Open Access


    Ground-Based Cloud Recognition Based on Dense_SIFT Features

    Zhizheng Zhang1, Jing Feng1,*, Jun Yan2, Xiaolei Wang1, Xiaocun Shu1

    Journal of New Media, Vol.1, No.1, pp. 1-9, 2019, DOI:10.32604/jnm.2019.05937

    Abstract Clouds play an important role in modulating radiation processes and climate changes in the Earth's atmosphere. Currently, measurement of meteorological elements such as temperature, air pressure, humidity, and wind has been automated. However, the cloud's automatic identification technology is still not perfect. Thus, this paper presents an approach that extracts dense scale-invariant feature transform (Dense_SIFT) as the local features of four typical cloud images. The extracted cloud features are then clustered by K-means algorithm, and the bag-of-words (BoW) model is used to describe each ground-based cloud image. Finally, support vector machine (SVM) is used for classification and recognition. Based on… More >

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