Journal of Artificial Intelligence

Journal on Artificial Intelligence

ISSN: 2579-0021 (print)
ISSN: 2579-003X (online) Publication Frequency: Quarterly

About the Journal

Artificial Intelligence (AI) techniques have been attracted increasing attention around the world and are now being widely used to solve a whole range of hitherto intractable problems. This journal welcomes foundational and applied papers describing mature work involving AI methods.

Current Issue - Vol.3, No.2, 2021 Most Viewed

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ARTICLE
A Generation Method of Letter-Level Adversarial Samples
Huixuan Xu¹, Chunlai Du¹, Yanhui Guo^2,*, Zhijian Cui¹, Haibo Bai¹
Journal on Artificial Intelligence, Vol.3, No.2, pp. 45-53, 2021, DOI:10.32604/jai.2021.016305
Abstract In recent years, with the rapid development of natural language processing, the security issues related to it have attracted more and more attention. Character perturbation is a common security problem. It can try to completely modify the input classification judgment of the target program without people’s attention by adding, deleting, or replacing several characters, which can reduce the effectiveness of the classifier. Although the current research has provided various methods of perturbation attacks on characters, the success rate of some methods is still not ideal. This paper mainly studies the sample generation of optimal perturbation characters and proposes a characterlevel… More
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ARTICLE
Evaluation Model of Farmer Training Effect Based on AHP–A Case Study of Hainan Province
Shengjie Li, Chaosheng Tang^*
Journal on Artificial Intelligence, Vol.3, No.2, pp. 55-62, 2021, DOI:10.32604/jai.2021.017408
Abstract On the basis of studying the influencing factors of training effect evaluation, this paper constructs an AHP-fuzzy comprehensive evaluation model for farmers’ vocational training activities in Hainan Province to evaluate farmers’ training effect, which overcomes the limitations of traditional methods. Firstly, the content and index system of farmer training effect evaluation are established by analytic hierarchy process, and the weight value of each index is determined. Then, the fuzzy comprehensive evaluation (FCE) of farmer training effect is carried out by using multi-level FCE. The joint use of AHP and FCE improves the reliability and effectiveness of the evaluation process and… More
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ARTICLE
Hybrid Efficient Convolution Operators for Visual Tracking
Yu Wang^*
Journal on Artificial Intelligence, Vol.3, No.2, pp. 63-72, 2021, DOI:10.32604/jai.2021.010455
Abstract Visual tracking is a classical computer vision problem with many applications. Efficient convolution operators (ECO) is one of the most outstanding visual tracking algorithms in recent years, it has shown great performance using discriminative correlation filter (DCF) together with HOG, color maps and VGGNet features. Inspired by new deep learning models, this paper propose a hybrid efficient convolution operators integrating fully convolution network (FCN) and residual network (ResNet) for visual tracking, where FCN and ResNet are introduced in our proposed method to segment the objects from backgrounds and extract hierarchical feature maps of objects, respectively. Compared with the traditional VGGNet,… More
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ARTICLE
Semantic Link Network Based Knowledge Graph Representation and Construction
Weiyu Guo^1,*, Ruixiang Jia¹, Ying Zhang²
Journal on Artificial Intelligence, Vol.3, No.2, pp. 73-79, 2021, DOI:10.32604/jai.2021.018648
Abstract A knowledge graph consists of a set of interconnected typed entities and their attributes, which shows a better performance to organize, manage and understand knowledge. However, because knowledge graphs contain a lot of knowledge triples, it is difficult to directly display to researchers. Semantic Link Network is an attempt, and it can deal with the construction, representation and reasoning of semantics naturally. Based on the Semantic Link Network, this paper explores the representation and construction of knowledge graph, and develops an academic knowledge graph prototype system to realize the representation, construction and visualization of knowledge graph. More
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Survey of Knowledge Graph Approaches and Applications
Hangjun Zhou¹, Tingting Shen^{1, *}, Xinglian Liu¹, Yurong Zhang¹, Peng Guo^{1, 2}, Jianjun Zhang³
Journal on Artificial Intelligence, Vol.2, No.2, pp. 89-101, 2020, DOI:10.32604/jai.2020.09968
Abstract With the advent of the era of big data, knowledge engineering has received extensive attention. How to extract useful knowledge from massive data is the key to big data analysis. Knowledge graph technology is an important part of artificial intelligence, which provides a method to extract structured knowledge from massive texts and images, and has broad application prospects. The knowledge base with semantic processing capability and open interconnection ability can be used to generate application value in intelligent information services such as intelligent search, intelligent question answering and personalized recommendation. Although knowledge graph has been applied to various systems, the… More
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ARTICLE
An Entropy-Based Model for Recommendation of Taxis’ Cruising Route
Yizhi Liu^{1, 2}, Xuesong Wang^{1, 2}, Jianxun Liu^{1, 2, *}, Zhuhua Liao^{1, 2}, Yijiang Zhao^{1, 2}, Jianjun Wang^{1, 2}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 137-148, 2020, DOI:10.32604/jai.2020.010620
Abstract Cruising route recommendation based on trajectory mining can improve taxidrivers' income and reduce energy consumption. However, existing methods mostly recommend pick-up points for taxis only. Moreover, their performance is not good enough since there lacks a good evaluation model for the pick-up points. Therefore, we propose an entropy-based model for recommendation of taxis' cruising route. Firstly, we select more positional attributes from historical pick-up points in order to obtain accurate spatial-temporal features. Secondly, the information entropy of spatial-temporal features is integrated in the evaluation model. Then it is applied for getting the next pick-up points and further recommending a series… More
Views:1450 Downloads:838 Download PDF

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Sentiment Analysis Using Deep Learning Approach
Peng Cen¹, Kexin Zhang¹, Desheng Zheng^{1, *}
Journal on Artificial Intelligence, Vol.2, No.1, pp. 17-27, 2020, DOI:10.32604/jai.2020.010132
Abstract Deep learning has made a great breakthrough in the field of speech and image recognition. Mature deep learning neural network has completely changed the field of nat ural language processing (NLP). Due to the enormous amount of data and opinions being produced, shared and transferred everyday across the Internet and other media, sentiment analysis has become one of the most active research fields in natural language processing. This paper introduces three deep learning networks applied in IMDB movie reviews sent iment analysis. Dataset was divided to 50% positive reviews and 50% negative reviews. Recurrent Neural Network (RNN) and Long Short-Term… More
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Impolite Pedestrian Detection by Using Enhanced YOLOv3-Tiny
Yanming Wang^{1, 2, 3}, Kebin Jia^{1, 2, 3}, Pengyu Liu^{1, 2, 3, *}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 113-124, 2020, DOI:10.32604/jai.2020.010137
Abstract In recent years, the problem of “Impolite Pedestrian” in front of the zebra crossing has aroused widespread concern from all walks of life. The traffic sector’s governance measures have become more serious. The traditional way of governance is onsite law enforcement, which requires a lot of manpower and material resources and is low efficiency. An enhanced YOLOv3-tiny model is proposed for pedestrians and vehicle detection in traffic monitoring. By modifying the backbone network structure of YOLOv3- tiny model, introducing deep detachable convolution operation, and designing the basic residual block unit of the network, the feature extraction ability of the backbone… More
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Research on Intelligent Technology Management and Service Platform
Ning Chen¹, Hui Li², Xinxin Fan^{3, 4}, Weiliang Kong¹, Yonghong Xie^{3, 4, *}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 149-155, 2020, DOI:10.32604/jai.2020.09888
Abstract In recent years, there are some problems in science and technology management, such as untimely task supervision and independent information system, which makes it difficult to achieve accurate, quantitative and standardized management. The storage of scientific research test data is scattered, and there are many deficiencies in the management, promotion and use of existing intellectual property. In this paper, on the basis of the knowledge economy, intelligence economy under the conditions of knowledge management concept and cutting-edge technology, technology management and service management related data, information, knowledge, method of blend together. Based on science and technology management, knowledge management as… More
Views:1204 Downloads:804 Download PDF

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Vehicle Target Detection Method Based on Improved SSD Model
Guanghui Yu¹, Honghui Fan¹, Hongyan Zhou¹, Tao Wu¹, Hongjin Zhu^{1, *}
Journal on Artificial Intelligence, Vol.2, No.3, pp. 125-135, 2020, DOI:10.32604/jai.2020.010501
Abstract When we use traditional computer vision Inspection technology to locate the vehicles, we find that the results were unsatisfactory, because of the existence of diversified scenes and uncertainty. So, we present a new method based on improved SSD model. We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model. Meanwhile, the new method optimizes the loss function, such as the loss function of predicted offset, and makes the loss function drop more smoothly near zero points. In addition, the new method improves cross entropy loss function of category prediction,… More
Views:1178 Downloads:873 Download PDF