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  • Open Access

    ARTICLE

    Modified Anam-Net Based Lightweight Deep Learning Model for Retinal Vessel Segmentation

    Syed Irtaza Haider1, Khursheed Aurangzeb2,*, Musaed Alhussein2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1501-1526, 2022, DOI:10.32604/cmc.2022.025479 - 18 May 2022

    Abstract The accurate segmentation of retinal vessels is a challenging task due to the presence of various pathologies as well as the low-contrast of thin vessels and non-uniform illumination. In recent years, encoder-decoder networks have achieved outstanding performance in retinal vessel segmentation at the cost of high computational complexity. To address the aforementioned challenges and to reduce the computational complexity, we propose a lightweight convolutional neural network (CNN)-based encoder-decoder deep learning model for accurate retinal vessels segmentation. The proposed deep learning model consists of encoder-decoder architecture along with bottleneck layers that consist of depth-wise squeezing, followed… More >

  • Open Access

    ARTICLE

    Lightweight Algorithm for MQTT Protocol to Enhance Power Consumption in Healthcare Environment

    Anwar D. Alhejaili*, Omar H. Alhazmi

    Journal on Internet of Things, Vol.4, No.1, pp. 21-33, 2022, DOI:10.32604/jiot.2022.019893 - 16 May 2022

    Abstract Internet of things (IoT) is used in various fields such as smart cities, smart home, manufacturing industries, and healthcare. Its application in healthcare has many advantages and disadvantages. One of its most common protocols is Message Queue Telemetry Transport (MQTT). MQTT protocol works as a publisher/subscriber which is suitable for IoT devices with limited power. One of the drawbacks of MQTT is that it is easy to manipulate. The default security provided by MQTT during user authentication, through username and password, does not provide any type of data encryption, to ensure confidentiality or integrity. This… More >

  • Open Access

    ARTICLE

    A Framework of Lightweight Deep Cross-Connected Convolution Kernel Mapping Support Vector Machines

    Qi Wang1, Zhaoying Liu1, Ting Zhang1,*, Shanshan Tu1, Yujian Li2, Muhammad Waqas3

    Journal on Artificial Intelligence, Vol.4, No.1, pp. 37-48, 2022, DOI:10.32604/jai.2022.027875 - 16 May 2022

    Abstract Deep kernel mapping support vector machines have achieved good results in numerous tasks by mapping features from a low-dimensional space to a high-dimensional space and then using support vector machines for classification. However, the depth kernel mapping support vector machine does not take into account the connection of different dimensional spaces and increases the model parameters. To further improve the recognition capability of deep kernel mapping support vector machines while reducing the number of model parameters, this paper proposes a framework of Lightweight Deep Convolutional Cross-Connected Kernel Mapping Support Vector Machines (LC-CKMSVM). The framework consists More >

  • Open Access

    ARTICLE

    Cold-Start Link Prediction via Weighted Symmetric Nonnegative Matrix Factorization with Graph Regularization

    Minghu Tang1,2,3,*, Wei Yu4, Xiaoming Li4, Xue Chen5, Wenjun Wang3, Zhen Liu6

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1069-1084, 2022, DOI:10.32604/csse.2022.028841 - 09 May 2022

    Abstract Link prediction has attracted wide attention among interdisciplinary researchers as an important issue in complex network. It aims to predict the missing links in current networks and new links that will appear in future networks. Despite the presence of missing links in the target network of link prediction studies, the network it processes remains macroscopically as a large connected graph. However, the complexity of the real world makes the complex networks abstracted from real systems often contain many isolated nodes. This phenomenon leads to existing link prediction methods not to efficiently implement the prediction of… More >

  • Open Access

    ARTICLE

    Deep Contextual Learning for Event-Based Potential User Recommendation in Online Social Networks

    T. Manojpraphakar*, A. Soundarrajan

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 699-713, 2022, DOI:10.32604/iasc.2022.025090 - 03 May 2022

    Abstract Event recommendation allows people to identify various recent upcoming social events. Based on the Profile or User recommendation people will identify the group of users to subscribe the event and to participate, despite it faces cold-start issues intrinsically. The existing models exploit multiple contextual factors to mitigate the cold-start issues in essential applications on profile recommendations to the event. However, those existing solution does not incorporate the correlation and covariance measures among various contextual factors. Moreover, recommending similar profiles to various groups of the events also has not been well analyzed in the existing literature.… More >

  • Open Access

    ARTICLE

    WDBM: Weighted Deep Forest Model Based Bearing Fault Diagnosis Method

    Letao Gao1,*, Xiaoming Wang2, Tao Wang3, Mengyu Chang4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4741-4754, 2022, DOI:10.32604/cmc.2022.027204 - 21 April 2022

    Abstract In the research field of bearing fault diagnosis, classical deep learning models have the problems of too many parameters and high computing cost. In addition, the classical deep learning models are not effective in the scenario of small data. In recent years, deep forest is proposed, which has less hyper parameters and adaptive depth of deep model. In addition, weighted deep forest (WDF) is proposed to further improve deep forest by assigning weights for decisions trees based on the accuracy of each decision tree. In this paper, weighted deep forest model-based bearing fault diagnosis method More >

  • Open Access

    ARTICLE

    Lightweight Authentication Protocol Based on Physical Unclonable Function

    Hanguang Luo1, Tao Zou1,*, Chunming Wu2, Dan Li3, Shunbin Li1, Chu Chu4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5031-5040, 2022, DOI:10.32604/cmc.2022.027118 - 21 April 2022

    Abstract In the emerging Industrial Internet of Things (IIoT), authentication problems have become an urgent issue for massive resource-constrained devices because traditional costly security mechanisms are not suitable for them. The security protocol designed for resource-constrained systems should not only be secure but also efficient in terms of usage of energy, storage, and processing. Although recently many lightweight schemes have been proposed, to the best of our knowledge, they are unable to address the problem of privacy preservation with the resistance of Denial of Service (DoS) attacks in a practical way. In this paper, we propose More >

  • Open Access

    ARTICLE

    Improved Lightweight Deep Learning Algorithm in 3D Reconstruction

    Tao Zhang1,*, Yi Cao2

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5315-5325, 2022, DOI:10.32604/cmc.2022.027083 - 21 April 2022

    Abstract The three-dimensional (3D) reconstruction technology based on structured light has been widely used in the field of industrial measurement due to its many advantages. Aiming at the problems of high mismatch rate and poor real-time performance caused by factors such as system jitter and noise, a lightweight stripe image feature extraction algorithm based on You Only Look Once v4 (YOLOv4) network is proposed. First, Mobilenetv3 is used as the backbone network to effectively extract features, and then the Mish activation function and Complete Intersection over Union (CIoU) loss function are used to calculate the improved More >

  • Open Access

    ARTICLE

    Two-Dimensional Projection-Based Wireless Intrusion Classification Using Lightweight EfficientNet

    Muhamad Erza Aminanto1,2,*, Ibnu Rifqi Purbomukti3, Harry Chandra2, Kwangjo Kim4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5301-5314, 2022, DOI:10.32604/cmc.2022.026749 - 21 April 2022

    Abstract Internet of Things (IoT) networks leverage wireless communication protocols, which adversaries can exploit. Impersonation attacks, injection attacks, and flooding are several examples of different attacks existing in Wi-Fi networks. Intrusion Detection System (IDS) became one solution to distinguish those attacks from benign traffic. Deep learning techniques have been intensively utilized to classify the attacks. However, the main issue of utilizing deep learning models is projecting the data, notably tabular data, into an image. This study proposes a novel projection from wireless network attacks data into a grid-based image for feeding one of the Convolutional Neural… More >

  • Open Access

    ARTICLE

    Ant Colony Optimization-based Light Weight Container (ACO-LWC) Algorithm for Efficient Load Balancing

    K. Aruna1,*, G. Pradeep2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 205-219, 2022, DOI:10.32604/iasc.2022.024317 - 15 April 2022

    Abstract Container technology is the latest lightweight virtualization technology which is an alternate solution for virtual machines. Docker is the most popular container technology for creating and managing Linux containers. Containers appear to be the most suitable medium for use in dynamic development, packaging, shipping and many other information technology environments. The portability of the software through the movement of containers is appreciated by businesses and IT professionals. In the docker container, one or more processes may run simultaneously. The main objective of this work is to propose a new algorithm called Ant Colony Optimization-based Light… More >

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