About the Journal
Journal of New Media (JNM) aims to provide a high quality and timely forum for researchers, engineers whose research interests focus on digital multimedia processing to share their state-of-the-art achievements, to learn the multimedia processing developments.
Indexing and Abstracting
Starting from July 2023, Journal of New Media will transition to a continuous publication model, accepted articles will be promptly published online upon completion of the peer review and production processes.
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Open Access
ARTICLE
Design of Artificial Intelligence Companion Chatbot
Journal of New Media, Vol.6, pp. 1-16, 2024, DOI:10.32604/jnm.2024.045833 - 28 March 2024
Abstract With the development of cities and the prevalence of networks, interpersonal relationships have become increasingly distant. When people crave communication, they hope to find someone to confide in. With the rapid advancement of deep learning and big data technologies, an enabling environment has been established for the development of intelligent chatbot systems. By effectively combining cutting-edge technologies with human-centered design principles, chatbots hold the potential to revolutionize our lives and alleviate feelings of loneliness. A multi-topic chat companion robot based on a state machine has been proposed, which can engage in fluent dialogue with humans… More >
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Open Access
ARTICLE
Key Frame Extraction Algorithm of Surveillance Video Based on Quaternion Fourier Significance Detection
Journal of New Media, Vol.4, No.1, pp. 1-11, 2022, DOI:10.32604/jnm.2022.027054
Abstract With the improvement of people's security awareness, numerous monitoring equipment has been put into use, resulting in the explosive growth of surveillance video data. Key frame extraction technology is a paramount technology for improving video storage efficiency and enhancing the accuracy of video retrieval. It can extract key frame sets that can express video content from massive videos. However, the existing key frame extraction algorithms of surveillance video still have deficiencies, such as the destruction of image information integrity and the inability to extract key frames accurately. To this end, this paper proposes a key… More >
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Open Access
ARTICLE
Research on Image Quality Enhancement Algorithm Using Hessian Matrix
Journal of New Media, Vol.4, No.3, pp. 117-123, 2022, DOI:10.32604/jnm.2022.027060
Abstract The Hessian matrix has a wide range of applications in image processing, such as edge detection, feature point detection, etc. This paper proposes an image enhancement algorithm based on the Hessian matrix. First, the Hessian matrix is obtained by convolving the derivative of the Gaussian function. Then use the Hessian matrix to enhance the linear structure in the image. Experimental results show that the method proposed in this paper has strong robustness and accuracy. More >
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Open Access
ARTICLE
Design of Middle School Chemistry Experiment Simulation System Based on Apriori Algorithm
Journal of New Media, Vol.4, No.1, pp. 41-50, 2022, DOI:10.32604/jnm.2022.027883
Abstract Aiming at the safety problems of toxic, flammable and explosive chemicals used in middle school chemical experiments, such as human poisoning, skin corrosion, fire or explosion caused by improper experimental operation, a virtual simulation method of chemical experiments based on unity is proposed. Due to the need to analyze and compare the data in chemical experiments, summarize the experimental characteristics and data relevance. Therefore, based on the Apriori algorithm, this method deeply excavates the data obtained in the chemical experiment, uses Maya to model the experimental environment, uses unity to design the interactive functions in… More >
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Open Access
REVIEW
Analysis of Campus Network Security
Journal of New Media, Vol.4, No.4, pp. 219-229, 2022, DOI:10.32604/jnm.2022.034830
Abstract Campus network provides a critical stage to student service and campus administration, which assumes a paramount part in the strategy of ‘Rejuvenating the Country through Science and Education’ and ‘Revitalizing China through Talented Persons’. However, with the rapid development and continuous expansion of campus network, network security needs to be an essential issue that could not be overlooked in campus network construction. In order to ensure the normal operation of various functions of the campus network, the security risk level of the campus network is supposed to be controlled within a reasonable range at any More >
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Open Access
ARTICLE
Vehicle Matching Based on Similarity Metric Learning
Journal of New Media, Vol.4, No.1, pp. 51-58, 2022, DOI:10.32604/jnm.2022.028775
Abstract With the development of new media technology, vehicle matching plays a further significant role in video surveillance systems. Recent methods explored the vehicle matching based on the feature extraction. Meanwhile, similarity metric learning also has achieved enormous progress in vehicle matching. But most of these methods are less effective in some realistic scenarios where vehicles usually be captured in different times. To address this cross-domain problem, we propose a cross-domain similarity metric learning method that utilizes the GAN to generate vehicle images with another domain and propose the two-channel Siamese network to learn a similarity More >
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Open Access
ARTICLE
Cross-Modal Relation-Aware Networks for Fake News Detection
Journal of New Media, Vol.4, No.1, pp. 13-26, 2022, DOI:10.32604/jnm.2022.027312
Abstract With the speedy development of communication Internet and the widespread use of social multimedia, so many creators have published posts on social multimedia platforms that fake news detection has already been a challenging task. Although some works use deep learning methods to capture visual and textual information of posts, most existing methods cannot explicitly model the binary relations among image regions or text tokens to mine the global relation information in a modality deeply such as image or text. Moreover, they cannot fully exploit the supplementary cross-modal information, including image and text relations, to supplement… More >
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Open Access
ARTICLE
Menu Text Recognition of Few-shot Learning
Journal of New Media, Vol.4, No.3, pp. 137-143, 2022, DOI:10.32604/jnm.2022.027890
Abstract Recent advances in OCR show that end-to-end (E2E) training pipelines including detection and identification can achieve the best results. However, many existing methods usually focus on case insensitive English characters. In this paper, we apply an E2E approach, the multiplex multilingual mask TextSpotter, which performs script recognition at the word level and uses different recognition headers to process different scripts while maintaining uniform loss, thus optimizing script recognition and multiple recognition headers simultaneously. Experiments show that this method is superior to the single-head model with similar number of parameters in end-to-end identification tasks. More >
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Open Access
ARTICLE
No-Reference Stereo Image Quality Assessment Based on Transfer Learning
Journal of New Media, Vol.4, No.3, pp. 125-135, 2022, DOI:10.32604/jnm.2022.027199
Abstract In order to apply the deep learning to the stereo image quality evaluation, two problems need to be solved: The first one is that we have a bit of training samples, another is how to input the dimensional image’s left view or right view. In this paper, we transfer the 2D image quality evaluation model to the stereo image quality evaluation, and this method solves the first problem; use the method of principal component analysis is used to fuse the left and right views into an input image in order to solve the second problem. More >
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Open Access
ARTICLE
Semi-Supervised Medical Image Segmentation Based on Generative Adversarial Network
Journal of New Media, Vol.4, No.3, pp. 155-164, 2022, DOI:10.32604/jnm.2022.031113
Abstract At present, segmentation for medical image is mainly based on fully supervised model training, which consumes a lot of time and labor for dataset labeling. To address this issue, we propose a semi-supervised medical image segmentation model based on a generative adversarial network framework for automated segmentation of arteries. The network is mainly composed of two parts: a segmentation network for medical image segmentation and a discriminant network for evaluating segmentation results. In the initial stage of network training, a fully supervised training method is adopted to make the segmentation network and the discrimination network More >
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Open Access
ARTICLE
Image Super-Resolution Reconstruction Based on Dual Residual Network
Journal of New Media, Vol.4, No.1, pp. 27-39, 2022, DOI:10.32604/jnm.2022.027826
Abstract Research shows that deep learning algorithms can effectively improve a single image's super-resolution quality. However, if the algorithm is solely focused on increasing network depth and the desired result is not achieved, difficulties in the training process are more likely to arise. Simultaneously, the function space that can be transferred from a low-resolution image to a high-resolution image is enormous, making finding a satisfactory solution difficult. In this paper, we propose a deep learning method for single image super-resolution. The MDRN network framework uses multi-scale residual blocks and dual learning to fully acquire features in… More >
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Open Access
ARTICLE
Feature Selection Based on Distance Measurement
Journal of New Media, Vol.3, No.1, pp. 19-27, 2021, DOI:10.32604/jnm.2021.018267
Abstract Every day we receive a large amount of information through different
social media and software, and this data and information can be realized with the
advent of data mining methods. In the process of data mining, to solve some
high-dimensional problems, feature selection is carried out in limited training
samples, and effective features are selected. This paper focuses on two Relief
feature selection algorithms: Relief and ReliefF algorithm. The differences
between them and their respective applicable scopes are analyzed. Based on
Relief algorithm, the high weight feature subset is obtained, and the correlation
between features More >
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Open Access
ARTICLE
Blockchain-Based Decentralized Reputation Management System for Internet of Everything in 6G-Enabled Cybertwin Architecture
Journal of New Media, Vol.3, No.4, pp. 137-150, 2021, DOI:10.32604/jnm.2021.024543
Abstract Internet of Everything (IoE) has emerged as a promising paradigm for
the purpose of connecting and exchanging data among physical objects and
humans over the Internet, and it can be widely applied in the fields of industry,
transportation, commerce, and education. Recently, the emergence of 6G-enabled
cybertwin network architecture provides the technical and theoretical foundation
for the realization of IoE paradigm. However, the IoE has three open issues in the
6G-enabled cybertwin architecture, i.e., data authenticity, data storage and node
reliability. To address these issues, we propose a blockchain-based decentralized
reputation management system (BC-DRMS)… More >
Copyright © 2024 The Author(s). Published by Tech Science Press.
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