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  • Open Access


    A Weighted Multi-Layer Analytics Based Model for Emoji Recommendation

    Amira M. Idrees1,*, Abdul Lateef Marzouq Al-Solami2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1115-1133, 2024, DOI:10.32604/cmc.2023.046457

    Abstract The developed system for eye and face detection using Convolutional Neural Networks (CNN) models, followed by eye classification and voice-based assistance, has shown promising potential in enhancing accessibility for individuals with visual impairments. The modular approach implemented in this research allows for a seamless flow of information and assistance between the different components of the system. This research significantly contributes to the field of accessibility technology by integrating computer vision, natural language processing, and voice technologies. By leveraging these advancements, the developed system offers a practical and efficient solution for assisting blind individuals. The modular design ensures flexibility, scalability, and… More >

  • Open Access


    Fusion of Hash-Based Hard and Soft Biometrics for Enhancing Face Image Database Search and Retrieval

    Ameerah Abdullah Alshahrani*, Emad Sami Jaha, Nahed Alowidi

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3489-3509, 2023, DOI:10.32604/cmc.2023.044490

    Abstract The utilization of digital picture search and retrieval has grown substantially in numerous fields for different purposes during the last decade, owing to the continuing advances in image processing and computer vision approaches. In multiple real-life applications, for example, social media, content-based face picture retrieval is a well-invested technique for large-scale databases, where there is a significant necessity for reliable retrieval capabilities enabling quick search in a vast number of pictures. Humans widely employ faces for recognizing and identifying people. Thus, face recognition through formal or personal pictures is increasingly used in various real-life applications, such as helping crime investigators… More >

  • Open Access


    Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

    Jianfeng Zhao1,2, Yunliang Huo1,2, Ji Xiong1,*, Junbo Liu1,2, Zhixing Guo1, Qingxian Li3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1663-1678, 2024, DOI:10.32604/cmes.2023.030584

    Abstract To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform, a case-based reasoning framework is proposed. Specifically, a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties. In addition, AHP (Analytic Hierarchy Process) and entropy weight method are integrated to provide features weight, where both user preferences and comprehensive impact of the index have been concerned. Grey relation analysis is used to obtain the similarity of a new problem and alternative cases. Finally, a platform is also… More >

  • Open Access


    Ontology-Based Crime News Semantic Retrieval System

    Fiaz Majeed1, Afzaal Ahmad1, Muhammad Awais Hassan2, Muhammad Shafiq3,*, Jin-Ghoo Choi3, Habib Hamam4,5,6,7

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 601-614, 2023, DOI:10.32604/cmc.2023.036074

    Abstract Every day, the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis. Crime news exists on the Internet in unstructured formats such as books, websites, documents, and journals. From such homogeneous data, it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies. Keyword-based Information Retrieval (IR) systems rely on statistics to retrieve results, making it difficult to obtain relevant results. They are unable to understand the user's query and thus face word mismatches due to context changes… More >

  • Open Access


    Retrieval of Winter Wheat Canopy Carotenoid Content with Ground- and Airborne-Based Hyperspectral Data

    Ting Cui, Xianfeng Zhou*, Yufeng Huang, Yanting Guo, Yunrui Lin, Leyi Song, Jingcheng Zhang

    Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2633-2648, 2023, DOI:10.32604/phyton.2023.029259

    Abstract Accurate assessment of canopy carotenoid content (CCx+cC) in crops is central to monitor physiological conditions in plants and vegetation stress, and consequently supporting agronomic decisions. However, due to the overlap of absorption peaks of carotenoid (Cx+c) and chlorophyll (Ca), accurate estimation of carotenoid using reflectance where carotenoid absorb is challenging. The objective of present study was to assess CCx+cC in winter wheat (Triticum aestivum L.) with ground- and aircraft-based hyperspectral measurements in the visible and near-infrared spectrum. In-situ hyperspectral reflectance were measured and airborne hyperspectral data were acquired during major growth stages of winter wheat in five consecutive field experiments.… More >

  • Open Access


    Pure Detail Feature Extraction Network for Visible-Infrared Re-Identification

    Jiaao Cui1, Sixian Chan1,2,*, Pan Mu1, Tinglong Tang2, Xiaolong Zhou3

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2263-2277, 2023, DOI:10.32604/iasc.2023.039894

    Abstract Cross-modality pedestrian re-identification has important applications in the field of surveillance. Due to variations in posture, camera perspective, and camera modality, some salient pedestrian features are difficult to provide effective retrieval cues. Therefore, it becomes a challenge to design an effective strategy to extract more discriminative pedestrian detail. Although many effective methods for detailed feature extraction are proposed, there are still some shortcomings in filtering background and modality noise. To further purify the features, a pure detail feature extraction network (PDFENet) is proposed for VI-ReID. PDFENet includes three modules, adaptive detail mask generation module (ADMG), inter-detail interaction module (IDI) and… More >

  • Open Access


    A Content-Based Medical Image Retrieval Method Using Relative Difference-Based Similarity Measure

    Ali Ahmed1,*, Alaa Omran Almagrabi2, Omar M. Barukab3

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2355-2370, 2023, DOI:10.32604/iasc.2023.039847

    Abstract Content-based medical image retrieval (CBMIR) is a technique for retrieving medical images based on automatically derived image features. There are many applications of CBMIR, such as teaching, research, diagnosis and electronic patient records. Several methods are applied to enhance the retrieval performance of CBMIR systems. Developing new and effective similarity measure and features fusion methods are two of the most powerful and effective strategies for improving these systems. This study proposes the relative difference-based similarity measure (RDBSM) for CBMIR. The new measure was first used in the similarity calculation stage for the CBMIR using an unweighted fusion method of traditional… More >

  • Open Access


    An Efficient Encrypted Speech Retrieval Based on Unsupervised Hashing and B+ Tree Dynamic Index

    Qiu-yu Zhang*, Yu-gui Jia, Fang-Peng Li, Le-Tian Fan

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 107-128, 2023, DOI:10.32604/cmc.2023.038911

    Abstract Existing speech retrieval systems are frequently confronted with expanding volumes of speech data. The dynamic updating strategy applied to construct the index can timely process to add or remove unnecessary speech data to meet users’ real-time retrieval requirements. This study proposes an efficient method for retrieving encryption speech, using unsupervised deep hashing and B+ tree dynamic index, which avoid privacy leakage of speech data and enhance the accuracy and efficiency of retrieval. The cloud’s encryption speech library is constructed by using the multi-threaded Dijk-Gentry-Halevi-Vaikuntanathan (DGHV) Fully Homomorphic Encryption (FHE) technique, which encrypts the original speech. In addition, this research employs… More >

  • Open Access


    Construction of Intelligent Recommendation Retrieval Model of FuJian Intangible Cultural Heritage Digital Archives Resources

    Xueqing Liao*

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 677-690, 2023, DOI:10.32604/iasc.2023.037219

    Abstract In order to improve the consistency between the recommended retrieval results and user needs, improve the recommendation efficiency, and reduce the average absolute deviation of resource retrieval, a design method of intelligent recommendation retrieval model for Fujian intangible cultural heritage digital archive resources based on knowledge atlas is proposed. The TG-LDA (Tag-granularity LDA) model is proposed on the basis of the standard LDA (Linear Discriminant Analysis) model. The model is used to mine archive resource topics. The Pearson correlation coefficient is used to measure the relevance between topics. Based on the measurement results, the FastText deep learning model is used… More >

  • Open Access


    A Sentence Retrieval Generation Network Guided Video Captioning

    Ou Ye1,2, Mimi Wang1, Zhenhua Yu1,*, Yan Fu1, Shun Yi1, Jun Deng2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5675-5696, 2023, DOI:10.32604/cmc.2023.037503

    Abstract Currently, the video captioning models based on an encoder-decoder mainly rely on a single video input source. The contents of video captioning are limited since few studies employed external corpus information to guide the generation of video captioning, which is not conducive to the accurate description and understanding of video content. To address this issue, a novel video captioning method guided by a sentence retrieval generation network (ED-SRG) is proposed in this paper. First, a ResNeXt network model, an efficient convolutional network for online video understanding (ECO) model, and a long short-term memory (LSTM) network model are integrated to construct… More >

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