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  • Open Access

    ARTICLE

    Clustering Algorithms: Taxonomy, Comparison, and Empirical Analysis in 2D Datasets

    Samih M. Mostafa1,2,*

    Journal on Artificial Intelligence, Vol.2, No.4, pp. 189-215, 2020, DOI:10.32604/jai.2020.014944 - 31 December 2020

    Abstract Because of the abundance of clustering methods, comparing between methods and determining which method is proper for a given dataset is crucial. Especially, the availability of huge experimental datasets and transactional and the emerging requirements for data mining and the like needs badly for clustering algorithms that can be applied in various domains. This paper presents essential notions of clustering and offers an overview of the significant features of the most common representative clustering algorithms of clustering categories presented in a comparative way. More specifically the study is based on the numerical type of the More >

  • Open Access

    ARTICLE

    A Learning Framework for Intelligent Selection of Software Verification Algorithms

    Weipeng Cao1, Zhongwu Xie1, Xiaofei Zhou2, Zhiwu Xu1, Cong Zhou1, Georgios Theodoropoulos3, Qiang Wang3,*

    Journal on Artificial Intelligence, Vol.2, No.4, pp. 177-187, 2020, DOI:10.32604/jai.2020.014829 - 31 December 2020

    Abstract Software verification is a key technique to ensure the correctness of software. Although numerous verification algorithms and tools have been developed in the past decades, it is still a great challenge for engineers to accurately and quickly choose the appropriate verification techniques for the software at hand. In this work, we propose a general learning framework for the intelligent selection of software verification algorithms, and instantiate the framework with two state-of-the-art learning algorithms: Broad learning (BL) and deep learning (DL). The experimental evaluation shows that the training efficiency of the BL-based model is much higher More >

  • Open Access

    ARTICLE

    Vehicle License Plate Recognition System Based on Deep Learning in Natural Scene

    Ze Chen, Leiming Yan*, Siran Yin, Yuanmin Shi

    Journal on Artificial Intelligence, Vol.2, No.4, pp. 167-175, 2020, DOI:10.32604/jai.2020.012716 - 31 December 2020

    Abstract With the popularity of intelligent transportation system, license plate recognition system has been widely used in the management of vehicles in and out of closed communities. But in the natural environment such as video monitoring, the performance and accuracy of recognition are not ideal. In this paper, the improved Alex net convolution neural network is used to remove the false license plate in a large range of suspected license plate areas, and then the projection transformation and Hough transformation are used to correct the inclined license plate, so as to build an efficient license plate More >

  • Open Access

    ARTICLE

    A Survey of Knowledge Based Question Answering with Deep Learning

    Chaoyu Deng, Guangfu Zeng, Zhiping Cai, Xiaoqiang Xiao*

    Journal on Artificial Intelligence, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jai.2020.011541 - 31 December 2020

    Abstract The purpose of automated question answering is to let the machine understand natural language questions and give accurate answers in the form of natural language. This technology requires the machine to store a large amount of background knowledge. In recent years, the rapid development of knowledge graph has made the knowledge based question answering (KBQA) more and more popular. Traditional styles of KBQA methods mainly include semantic parsing, information extraction and vector modeling. With the development of deep learning, KBQA with deep learning has gradually become the mainstream method. This paper introduces the application of More >

  • Open Access

    ARTICLE

    Research on Intelligent Technology Management and Service Platform

    Ning Chen1, Hui Li2, Xinxin Fan3, 4, Weiliang Kong1, Yonghong Xie3, 4, *

    Journal on Artificial Intelligence, Vol.2, No.3, pp. 149-155, 2020, DOI:10.32604/jai.2020.09888 - 15 July 2020

    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 More >

  • Open Access

    ARTICLE

    An Entropy-Based Model for Recommendation of Taxis’ Cruising Route

    Yizhi Liu1, 2, Xuesong Wang1, 2, Jianxun Liu1, 2, *, Zhuhua Liao1, 2, Yijiang Zhao1, 2, Jianjun Wang1, 2

    Journal on Artificial Intelligence, Vol.2, No.3, pp. 137-148, 2020, DOI:10.32604/jai.2020.010620 - 15 July 2020

    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 More >

  • Open Access

    ARTICLE

    Vehicle Target Detection Method Based on Improved SSD Model

    Guanghui Yu1, Honghui Fan1, Hongyan Zhou1, Tao Wu1, Hongjin Zhu1, *

    Journal on Artificial Intelligence, Vol.2, No.3, pp. 125-135, 2020, DOI:10.32604/jai.2020.010501 - 15 July 2020

    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 More >

  • Open Access

    ARTICLE

    Impolite Pedestrian Detection by Using Enhanced YOLOv3-Tiny

    Yanming Wang1, 2, 3, Kebin Jia1, 2, 3, Pengyu Liu1, 2, 3, *

    Journal on Artificial Intelligence, Vol.2, No.3, pp. 113-124, 2020, DOI:10.32604/jai.2020.010137 - 15 July 2020

    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… More >

  • Open Access

    ARTICLE

    An Attention-Based Recognizer for Scene Text

    Yugang Li1, *, Haibo Sun1

    Journal on Artificial Intelligence, Vol.2, No.2, pp. 103-112, 2020, DOI:10.32604/jai.2020.010203 - 15 July 2020

    Abstract Scene text recognition (STR) is the task of recognizing character sequences in natural scenes. Although STR method has been greatly developed, the existing methods still can't recognize any shape of text, such as very rich curve text or rotating text in daily life, irregular scene text has complex layout in two-dimensional space, which is used to recognize scene text in the past Recently, some recognizers correct irregular text to regular text image with approximate 1D layout, or convert 2D image feature mapping to one-dimensional feature sequence. Although these methods have achieved good performance, their robustness More >

  • Open Access

    ARTICLE

    Survey of Knowledge Graph Approaches and Applications

    Hangjun Zhou1, Tingting Shen1, *, Xinglian Liu1, Yurong Zhang1, Peng Guo1, 2, Jianjun Zhang3

    Journal on Artificial Intelligence, Vol.2, No.2, pp. 89-101, 2020, DOI:10.32604/jai.2020.09968 - 15 July 2020

    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 More >

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