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  • Open Access

    ARTICLE

    Pre-Trained Deep Neural Network-Based Computer-Aided Breast Tumor Diagnosis Using ROI Structures

    Venkata Sunil Srikanth*, S. Krithiga

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 63-78, 2023, DOI:10.32604/iasc.2023.023474 - 06 June 2022

    Abstract Deep neural network (DNN) based computer-aided breast tumor diagnosis (CABTD) method plays a vital role in the early detection and diagnosis of breast tumors. However, a Brightness mode (B-mode) ultrasound image derives training feature samples that make closer isolation toward the infection part. Hence, it is expensive due to a meta-heuristic search of features occupying the global region of interest (ROI) structures of input images. Thus, it may lead to the high computational complexity of the pre-trained DNN-based CABTD method. This paper proposes a novel ensemble pre-trained DNN-based CABTD method using global- and local-ROI-structures of… More >

  • Open Access

    ARTICLE

    Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

    M. Rajakani1,*, R. J. Kavitha2, A. Ramachandran3

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 265-280, 2023, DOI:10.32604/csse.2023.024994 - 01 June 2022

    Abstract Feature extraction is the most critical step in classification of multispectral image. The classification accuracy is mainly influenced by the feature sets that are selected to classify the image. In the past, handcrafted feature sets are used which are not adaptive for different image domains. To overcome this, an evolutionary learning method is developed to automatically learn the spatial-spectral features for classification. A modified Firefly Algorithm (FA) which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose. For extracting the most efficient More >

  • Open Access

    ARTICLE

    A Lightweight Driver Drowsiness Detection System Using 3DCNN With LSTM

    Sara A. Alameen*, Areej M. Alhothali

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 895-912, 2023, DOI:10.32604/csse.2023.024643 - 01 June 2022

    Abstract Today, fatalities, physical injuries, and significant economic losses occur due to car accidents. Among the leading causes of car accidents is drowsiness behind the wheel, which can affect any driver. Drowsiness and sleepiness often have associated indicators that researchers can use to identify and promptly warn drowsy drivers to avoid potential accidents. This paper proposes a spatiotemporal model for monitoring drowsiness visual indicators from videos. This model depends on integrating a 3D convolutional neural network (3D-CNN) and long short-term memory (LSTM). The 3DCNN-LSTM can analyze long sequences by applying the 3D-CNN to extract spatiotemporal features… More >

  • Open Access

    ARTICLE

    Arrhythmia Prediction on Optimal Features Obtained from the ECG as Images

    Fuad A. M. Al-Yarimi*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 129-142, 2023, DOI:10.32604/csse.2023.024297 - 01 June 2022

    Abstract A critical component of dealing with heart disease is real-time identification, which triggers rapid action. The main challenge of real-time identification is illustrated here by the rare occurrence of cardiac arrhythmias. Recent contributions to cardiac arrhythmia prediction using supervised learning approaches generally involve the use of demographic features (electronic health records), signal features (electrocardiogram features as signals), and temporal features. Since the signal of the electrical activity of the heartbeat is very sensitive to differences between high and low heartbeats, it is possible to detect some of the irregularities in the early stages of arrhythmia. More >

  • Open Access

    ARTICLE

    Brain Tumor Segmentation through Level Based Learning Model

    K. Dinesh Babu1,*, C. Senthil Singh2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 709-720, 2023, DOI:10.32604/csse.2023.024295 - 01 June 2022

    Abstract Brain tumors are potentially fatal presence of cancer cells over a human brain, and they need to be segmented for accurate and reliable planning of diagnosis. Segmentation process must be carried out in different regions based on which the stages of cancer can be accurately derived. Glioma patients exhibit a different level of challenge in terms of cancer or tumors detection as the Magnetic Resonance Imaging (MRI) images possess varying sizes, shapes, positions, and modalities. The scanner used for sensing the location of tumors cells will be subjected to additional protocols and measures for accuracy,… More >

  • Open Access

    ARTICLE

    Skin Lesion Classification System Using Shearlets

    S. Mohan Kumar*, T. Kumanan

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 833-844, 2023, DOI:10.32604/csse.2023.022385 - 01 June 2022

    Abstract The main cause of skin cancer is the ultraviolet radiation of the sun. It spreads quickly to other body parts. Thus, early diagnosis is required to decrease the mortality rate due to skin cancer. In this study, an automatic system for Skin Lesion Classification (SLC) using Non-Subsampled Shearlet Transform (NSST) based energy features and Support Vector Machine (SVM) classifier is proposed. At first, the NSST is used for the decomposition of input skin lesion images with different directions like 2, 4, 8 and 16. From the NSST’s sub-bands, energy features are extracted and stored in More >

  • Open Access

    ARTICLE

    Iris Recognition Based on Multilevel Thresholding Technique and Modified Fuzzy c-Means Algorithm

    Slim Ben Chaabane1,2,*, Rafika Harrabi1,2, Anas Bushnag1, Hassene Seddik2

    Journal on Artificial Intelligence, Vol.4, No.4, pp. 201-214, 2022, DOI:10.32604/jai.2022.032850 - 25 May 2023

    Abstract Biometrics represents the technology for measuring the characteristics of the human body. Biometric authentication currently allows for secure, easy, and fast access by recognizing a person based on facial, voice, and fingerprint traits. Iris authentication is one of the essential biometric methods for identifying a person. This authentication type has become popular in research and practical applications. Unlike the face and hands, the iris is an internal organ, protected and therefore less likely to be damaged. However, the number of helpful information collected from the iris is much greater than the other biometric human organs.… More >

  • Open Access

    ARTICLE

    An Adaptive-Feature Centric XGBoost Ensemble Classifier Model for Improved Malware Detection and Classification

    J. Pavithra*, S. Selvakumarasamy

    Journal of Cyber Security, Vol.4, No.3, pp. 135-151, 2022, DOI:10.32604/jcs.2022.031889 - 01 February 2023

    Abstract Machine learning (ML) is often used to solve the problem of malware detection and classification, and various machine learning approaches are adapted to the problem of malware classification; still acquiring poor performance by the way of feature selection, and classification. To address the problem, an efficient novel algorithm for adaptive feature-centered XG Boost Ensemble Learner Classifier “AFC-XG Boost” is presented in this paper. The proposed model has been designed to handle varying data sets of malware detection obtained from Kaggle data set. The model turns the XG Boost classifier in several stages to optimize performance.… More >

  • Open Access

    ARTICLE

    Vibration-Based Fault Diagnosis Study on a Hydraulic Brake System Using Fuzzy Logic with Histogram Features

    Alamelu Manghai T Marimuthu1, Jegadeeshwaran Rakkiyannan2,*, Lakshmipathi Jakkamputi1, Sugumaran Vaithiyanathan1, Sakthivel Gnanasekaran2

    Structural Durability & Health Monitoring, Vol.16, No.4, pp. 383-396, 2022, DOI:10.32604/sdhm.2022.011396 - 03 January 2023

    Abstract The requirement of fault diagnosis in the field of automobiles is growing higher day by day. The reliability of human resources for the fault diagnosis is uncertain. Brakes are one of the major critical components in automobiles that require closer and active observation. This research work demonstrates a fault diagnosis technique for monitoring the hydraulic brake system using vibration analysis. Vibration signals of a rotating element contain dynamic information about its health condition. Hence, the vibration signals were used for the brake fault diagnosis study. The study was carried out on a brake fault diagnosis More >

  • Open Access

    ARTICLE

    Racial Disparities in Clinical Features and Survival Outcomes among Patients with Pancreatic Neuroendocrine Tumor: A Contemporary SEER Database Analysis

    Fei Wang1, Jihyun Ma2, Nan Zhao3, Chi Lin3,*, Haixing Jiang1,*

    Oncologie, Vol.24, No.4, pp. 865-895, 2022, DOI:10.32604/oncologie.2022.025447 - 31 December 2022

    Abstract Objective: The characteristics of clinical features and prognoses among patients with different racial backgrounds have not been clearly studied. We thus investigated the clinical characteristics and overall survival (OS) differences among Asian, White, and Black patients with pancreatic neuroendocrine tumors (pNETs). Materials and Methods: The Surveillance, Epidemiology, and End Results (SEER) database was queried to identify patients with pNETs between 1983 and 2015. We performed univariable (UVA) and multivariable logistic regression (MVA) to assess the association between variables and race category. A Kaplan-Meier (KM) plot was used to calculate the OS rates. The Cox proportional hazard regression… More >

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