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  • Open Access

    ARTICLE

    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

    ARTICLE

    MFF-Net: Multimodal Feature Fusion Network for 3D Object Detection

    Peicheng Shi1,*, Zhiqiang Liu1, Heng Qi1, Aixi Yang2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5615-5637, 2023, DOI:10.32604/cmc.2023.037794

    Abstract In complex traffic environment scenarios, it is very important for autonomous vehicles to accurately perceive the dynamic information of other vehicles around the vehicle in advance. The accuracy of 3D object detection will be affected by problems such as illumination changes, object occlusion, and object detection distance. To this purpose, we face these challenges by proposing a multimodal feature fusion network for 3D object detection (MFF-Net). In this research, this paper first uses the spatial transformation projection algorithm to map the image features into the feature space, so that the image features are in the same spatial dimension when fused… More >

  • Open Access

    ARTICLE

    3D Vehicle Detection Algorithm Based on Multimodal Decision-Level Fusion

    Peicheng Shi1,*, Heng Qi1, Zhiqiang Liu1, Aixi Yang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2007-2023, 2023, DOI:10.32604/cmes.2023.022304

    Abstract 3D vehicle detection based on LiDAR-camera fusion is becoming an emerging research topic in autonomous driving. The algorithm based on the Camera-LiDAR object candidate fusion method (CLOCs) is currently considered to be a more effective decision-level fusion algorithm, but it does not fully utilize the extracted features of 3D and 2D. Therefore, we proposed a 3D vehicle detection algorithm based on multimodal decision-level fusion. First, project the anchor point of the 3D detection bounding box into the 2D image, calculate the distance between 2D and 3D anchor points, and use this distance as a new fusion feature to enhance the… More > Graphic Abstract

    3D Vehicle Detection Algorithm Based on Multimodal Decision-Level Fusion

  • Open Access

    ARTICLE

    Liver Lesions and Acute Intracerebral Hemorrhage Detection Using Multimodal Fusion

    Osama S. Faragallah1,*, Abdullah N. Muhammed2, Taha S. Taha3, Gamal G. N. Geweid4,5

    Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 215-225, 2021, DOI:10.32604/iasc.2021.019058

    Abstract Medical image fusion is designed to help physicians in their decisions by providing them with a preclinical image with enough information. Accurate assessment and effective treatment of the disease reduce the time it takes to relieve the symptoms of the disease. This article utilizes an effective data fusion approach to work on two different imaging modalities; computed tomography (CT) and magnetic resonance imaging (MRI). The data fusion approach is based on the combination of singular value decomposition (SVD) and the Fast Discrete Curvelet Transform (FDCT) techniques to reduce processing time during the fusion process. The SVD-FDCT data fusion approach is… More >

  • Open Access

    ARTICLE

    Deep Learning Based Optimal Multimodal Fusion Framework for Intrusion Detection Systems for Healthcare Data

    Phong Thanh Nguyen1, Vy Dang Bich Huynh2, Khoa Dang Vo1, Phuong Thanh Phan1, Mohamed Elhoseny3, Dac-Nhuong Le4,5,*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2555-2571, 2021, DOI:10.32604/cmc.2021.012941

    Abstract Data fusion is a multidisciplinary research area that involves different domains. It is used to attain minimum detection error probability and maximum reliability with the help of data retrieved from multiple healthcare sources. The generation of huge quantity of data from medical devices resulted in the formation of big data during which data fusion techniques become essential. Securing medical data is a crucial issue of exponentially-pacing computing world and can be achieved by Intrusion Detection Systems (IDS). In this regard, since singular-modality is not adequate to attain high detection rate, there is a need exists to merge diverse techniques using… More >

  • Open Access

    ARTICLE

    Fusion of Medical Images in Wavelet Domain: A Hybrid Implementation

    Satya Prakash Yadav1, *, Sachin Yadav2

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 303-321, 2020, DOI:10.32604/cmes.2020.08459

    Abstract This paper presents a low intricate, profoundly energy effective MRI Images combination intended for remote visual sensor frameworks which leads to improved understanding and implementation of treatment; especially for radiology. This is done by combining the original picture which leads to a significant reduction in the computation time and frequency. The proposed technique conquers the calculation and energy impediment of low power tools and is examined as far as picture quality and energy is concerned. Reenactments are performed utilizing MATLAB 2018a, to quantify the resultant vitality investment funds and the reproduction results show that the proposed calculation is very quick… More >

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