Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (930)
  • Open Access

    ARTICLE

    Tracking Features in Image Sequences with Kalman Filtering, Global Optimization, Mahalanobis Distance and a Management Model

    Raquel R. Pinho1, João Manuel R. S. Tavares1

    CMES-Computer Modeling in Engineering & Sciences, Vol.46, No.1, pp. 51-76, 2009, DOI:10.3970/cmes.2009.046.051

    Abstract This work addresses the problem of tracking feature points along image sequences. In order to analyze the undergoing movement, an approach based on the Kalman filtering technique has been used, which basically carries out the estimation and correction of the features' movement in every image frame. So as to integrate the measurements obtained from each image into the Kalman filter, a data optimization process has been adopted to achieve the best global correspondence set. The proposed criterion minimizes the cost of global matching, which is based on the Mahalanobis distance. A management model is employed to manage the features being… More >

  • Open Access

    ARTICLE

    Flow Features and Industrial Applications of TSE Rheoextrusion Process

    H. Tang1, L.C. Wrobel2, Z. Fan2

    FDMP-Fluid Dynamics & Materials Processing, Vol.3, No.2, pp. 129-146, 2007, DOI:10.3970/fdmp.2007.003.129

    Abstract This paper presents an overview of diverse extrusion techniques and, in particular, a focused discussion about the rheoextrusion process for semi-solid casting (a novel casting process for the fabrication of high quality metals). The review reveals a wealth of interesting rheological and microstructural features, illustrating qualitative and quantitative data. The analysis is supported by relevant numerical results and examples. It is shown how numerical studies can lead to significant insights into these processes by providing more detailed information on the fundamental mechanisms of morphology development (during phase change) and profile forming. The die filling and solidification behaviours within extrusion dies… More >

  • Open Access

    ARTICLE

    Fast Scene Reconstruction Based on Improved SLAM

    Zhenlong Du1,*, Yun Ma1, Xiaoli Li1, Huimin Lu2

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 243-254, 2019, DOI:10.32604/cmc.2019.05961

    Abstract Simultaneous location and mapping (SLAM) plays the crucial role in VR/AR application, autonomous robotics navigation, UAV remote control, etc. The traditional SLAM is not good at handle the data acquired by camera with fast movement or severe jittering, and the efficiency need to be improved. The paper proposes an improved SLAM algorithm, which mainly improves the real-time performance of classical SLAM algorithm, applies KDtree for efficient organizing feature points, and accelerates the feature points correspondence building. Moreover, the background map reconstruction thread is optimized, the SLAM parallel computation ability is increased. The color images experiments demonstrate that the improved SLAM… More >

  • Open Access

    ARTICLE

    Application of Self-Organizing Feature Map Neural Network Based on K-means Clustering in Network Intrusion Detection

    Ling Tan1,*, Chong Li2, Jingming Xia2, Jun Cao3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 275-288, 2019, DOI:10.32604/cmc.2019.03735

    Abstract Due to the widespread use of the Internet, customer information is vulnerable to computer systems attack, which brings urgent need for the intrusion detection technology. Recently, network intrusion detection has been one of the most important technologies in network security detection. The accuracy of network intrusion detection has reached higher accuracy so far. However, these methods have very low efficiency in network intrusion detection, even the most popular SOM neural network method. In this paper, an efficient and fast network intrusion detection method was proposed. Firstly, the fundamental of the two different methods are introduced respectively. Then, the self-organizing feature… More >

  • Open Access

    ARTICLE

    An Intrusion Detection Algorithm Based on Feature Graph

    Xiang Yu1, Zhihong Tian2, Jing Qiu2,*, Shen Su2,*, Xiaoran Yan3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 255-274, 2019, DOI:10.32604/cmc.2019.05821

    Abstract With the development of Information technology and the popularization of Internet, whenever and wherever possible, people can connect to the Internet optionally. Meanwhile, the security of network traffic is threatened by various of online malicious behaviors. The aim of an intrusion detection system (IDS) is to detect the network behaviors which are diverse and malicious. Since a conventional firewall cannot detect most of the malicious behaviors, such as malicious network traffic or computer abuse, some advanced learning methods are introduced and integrated with intrusion detection approaches in order to improve the performance of detection approaches. However, there are very few… More >

  • Open Access

    ARTICLE

    Development of an Ultrasonic Nomogram for Preoperative Prediction of Castleman Disease Pathological Type

    Xinfang Wang1, Lianqing Hong2, Xi Wu3, Jia He3, Ting Wang3,4,*, Hongbo Li5, Shaoling Liu6

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 141-154, 2019, DOI:10.32604/cmc.2019.06030

    Abstract An ultrasonic nomogram was developed for preoperative prediction of Castleman disease (CD) pathological type (hyaline vascular (HV) or plasma cell (PC) variant) to improve the understanding and diagnostic accuracy of ultrasound for this disease. Fifty cases of CD confirmed by pathology were gathered from January 2012 to October 2018 from three hospitals. A grayscale ultrasound image of each patient was collected and processed. First, the region of interest of each gray ultrasound image was manually segmented using a process that was guided and calibrated by radiologists who have been engaged in imaging diagnosis for more than 5 years. In addition,… More >

  • Open Access

    ARTICLE

    An Adaptive Superpixel Tracker Using Multiple Features

    Jingjing Liu1,2, Bin Zhang3, Xu Cheng4, Ying Chen5, Li Zhao1,*

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1097-1108, 2019, DOI:10.32604/cmc.2019.05968

    Abstract Visual tracking is a challenging issue in the field of computer vision due to the objects’ intricate appearance variation. To adapt the change of the appearance, multiple channel features which could provide more information are used. However, the low level feature could not represent the structure of the object. In this paper, a superpixel-based adaptive tracking algorithm by using color histogram and haar-like feature is proposed, whose feature is classified into the middle level. Based on the superpixel representation of video frames, the haar-like feature is extracted at the superpixel level as the local feature, and the color histogram feature… More >

  • Open Access

    ARTICLE

    Attention-Aware Network with Latent Semantic Analysis for Clothing Invariant Gait Recognition

    Hefei Ling1, Jia Wu1, Ping Li1,*, Jialie Shen2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1041-1054, 2019, DOI:10.32604/cmc.2019.05605

    Abstract Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes and capturing the relationships from… More >

  • Open Access

    ARTICLE

    Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

    B. V. Santhosh Krishna1, *, T. Gnanasekaran2

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 855-869, 2019, DOI:10.32604/cmc.2019.07585

    Abstract An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction… More >

  • Open Access

    ARTICLE

    Robust Re-Weighted Multi-View Feature Selection

    Yiming Xue1, Nan Wang2, Yan Niu1, Ping Zhong2, ∗, Shaozhang Niu3, Yuntao Song4

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 741-756, 2019, DOI:10.32604/cmc.2019.05611

    Abstract In practical application, many objects are described by multi-view features because multiple views can provide a more informative representation than the single view. When dealing with the multi-view data, the high dimensionality is often an obstacle as it can bring the expensive time consumption and an increased chance of over-fitting. So how to identify the relevant views and features is an important issue. The matrix-based multi-view feature selection that can integrate multiple views to select relevant feature subset has aroused widely concern in recent years. The existing supervised multi-view feature selection methods usually concatenate all views into the long vectors… More >

Displaying 911-920 on page 92 of 930. Per Page