دانلود مقاله انگلیسی رایگان:توصیف کننده تصویر مبتنی بر شبکه عصبی برای طبقه بندی بافت - 2019
بلافاصله پس از پرداخت دانلود کنید

با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد). 

دانلود مقاله انگلیسی تشخیص الگو رایگان
  • A novel neural network based image descriptor for texture classification A novel neural network based image descriptor for texture classification
    A novel neural network based image descriptor for texture classification

    دسته بندی:

    تشخیص الگو - Pattern recognition


    سال انتشار:

    2019


    عنوان انگلیسی مقاله:

    A novel neural network based image descriptor for texture classification


    ترجمه فارسی عنوان مقاله:

    توصیف کننده تصویر مبتنی بر شبکه عصبی برای طبقه بندی بافت


    منبع:

    Sciencedirect - Elsevier - Physica A, 526 (2019) 120955: doi:10:1016/j:physa:2019:04:191


    نویسنده:

    Turker Tuncer ∗, Sengul Dogan, Fatih Ertam


    چکیده انگلیسی:

    Nowadays, image processing and artificial intelligence have become popular science areas. The one of the major problems of the image processing is texture classification. Therefore, many methods have been presented about texture classification. In this article, a new textural feature extraction method is proposed. In this method, the feed forward neural networks are utilized as a feature extractor. The main purpose of the proposed method is to show feature extraction capability of the feed forward neural network. This descriptor consists of 3 x 3 overlapping blocks division, creating feature extraction network by using row and column pixels of the block, calculating feature value, normalization and histogram extraction. Firstly, image is divided into 3 x 3 size of overlapping blocks and pixels of each block are selected to create feed forward networks. To calculate the weights, neighbor pixel values and the signum function are used together. Tangent hyperbolic function is utilized as activation function in these networks. PCA (Principle Component Analysis) reduces feature dimensionality and LDA (Linear Discriminant Analysis) is chosen as classifier. In order to obtain the experimental results, the commonly used texture datasets were used with variable parameters. These datasets are UIUC, Outex and USPTex. The classification accuracies were calculated as 90.82%, 89.62% and 93.83% for these datasets respectively. The results were compared with the related 16 methods and the proposed method achieved the best performance among them. The space complexity of this method also calculated and the cost of the proposed method was given in the experiments. The computational costs result of this method demonstrates that the proposed neural network based image descriptor method has low complexity. The results clearly illustrated that the proposed textural image descriptor extracts distinctive features with short execution time, has simple mathematical background, is good discriminator and outperforms.
    Keywords: Feed forward textural feature extraction | Texture analysis | Texture recognition | Pattern recognition | Classification


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 11
    حجم فایل: 690 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




اگر این مقاله را پسندیدید آن را در شبکه های اجتماعی به اشتراک بگذارید (برای به اشتراک گذاری بر روی ایکن های زیر کلیک کنید)

تعداد نظرات : 0

الزامی
الزامی
الزامی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی
logo-samandehi
بازدید امروز: 1500 :::::::: بازدید دیروز: 0 :::::::: بازدید کل: 1500 :::::::: افراد آنلاین: 50