Home / Journals / JNM / Vol.4, No.2, 2022
  • Open AccessOpen Access

    ARTICLE

    Deep Feature Bayesian Classifier for SAR Target Recognition with Small Training Set

    Liguo Zhang1,2, Zilin Tian1, Yan Zhang3,*, Tong Shuai4, Shuo Liang4, Zhuofei Wu5
    Journal of New Media, Vol.4, No.2, pp. 59-71, 2022, DOI:10.32604/jnm.2022.029360
    Abstract In recent years, deep learning algorithms have been popular in recognizing targets in synthetic aperture radar (SAR) images. However, due to the problem of overfitting, the performance of these models tends to worsen when just a small number of training data are available. In order to solve the problems of overfitting and an unsatisfied performance of the network model in the small sample remote sensing image target recognition, in this paper, we uses a deep residual network to autonomously acquire image features and proposes the Deep Feature Bayesian Classifier model (RBnet) for SAR image target recognition. In the RBnet, a… More >

  • Open AccessOpen Access

    ARTICLE

    Prediction of Epileptic EEG Signal Based on SECNN-LSTM

    Jian Qiang Wang1, Wei Fang1,2,*, Victor S. Sheng3
    Journal of New Media, Vol.4, No.2, pp. 73-84, 2022, DOI:10.32604/jnm.2022.027040
    Abstract Brain-Computer Interface (BCI) technology is a way for humans to explore the mysteries of the brain and has applications in many areas of real life. People use this technology to capture brain waves and analyze the electroencephalograph (EEG) signal for feature extraction. Take the medical field as an example, epilepsy disease is threatening human health every moment. We propose a convolutional neural network SECNN-LSTM framework based on the attention mechanism can automatically perform feature extraction and analysis on the collected EEG signals of patients to complete the prediction of epilepsy diseases, overcoming the problem that the disease requires long time… More >

  • Open AccessOpen Access

    ARTICLE

    Blood Sample Image Classification Algorithm Based on SVM and HOG

    Tianyi Jiang1, Shuangshuang Ying2, Zhou Fang1, Xue Song1, Yinggang Sun2, Dongyang Zhan3,4, Chao Ma2,*
    Journal of New Media, Vol.4, No.2, pp. 85-95, 2022, DOI:10.32604/jnm.2022.027175
    Abstract In the medical field, the classification and analysis of blood samples has always been arduous work. In the previous work of this task, manual classification maneuvers have been used, which are time consuming and laborious. The conventional blood image classification research is mainly focused on the microscopic cell image classification, while the macroscopic reagent processing blood coagulation image classification research is still blank. These blood samples processed with reagents often show some inherent shape characteristics, such as coagulation, attachment, discretization and so on. The shape characteristics of these blood samples also make it possible for us to recognize their classification… More >

  • Open AccessOpen Access

    ARTICLE

    Skeleton Keypoints Extraction Method Combined with Object Detection

    Jiabao Shi1, Zhao Qiu1,*, Tao Chen1, Jiale Lin1, Hancheng Huang2, Yunlong He3, Yu Yang3
    Journal of New Media, Vol.4, No.2, pp. 97-106, 2022, DOI:10.32604/jnm.2022.027176
    Abstract Big data is a comprehensive result of the development of the Internet of Things and information systems. Computer vision requires a lot of data as the basis for research. Because skeleton data can adapt well to dynamic environment and complex background, it is used in action recognition tasks. In recent years, skeleton-based action recognition has received more and more attention in the field of computer vision. Therefore, the keypoints of human skeletons are essential for describing the pose estimation of human and predicting the action recognition of the human. This paper proposes a skeleton point extraction method combined with object… More >

  • Open AccessOpen Access

    ARTICLE

    T01067* Series Fuel Pump Pulp Molded Package Dynamic Drop Simulation

    W. Zhongliang1, C. Jiawen1, F. Li1, C. Yang1, Z. Hong1,2,*
    Journal of New Media, Vol.4, No.2, pp. 107-116, 2022, DOI:10.32604/jnm.2022.019753
    Abstract In this paper, combined with the actual situation encountered in the process of product transportation, the finite element analysis software ANSYS/LS-DYNA was used to simulate the dynamic drop process of the buffer packaging structure of T01067* series fuel pump, and the simulation results were analyzed, and a conclusion was drawn. According to the fuel pump weight calculation buffer material thickness, according to the product size and structure design of the pulp molded cushion structure, simulation of static cushioning performance, and dynamic drop simulation, for the subsequent structural optimization cost reduction to provide early warning [,]. Check the simulation production cost,… More >

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