Errata To "A Study Of Cloud Classification With Neural Networks Using Spectral And Textural Features"
نویسندگان
چکیده
Manuscript received March 1, 1999. B. Tian, M. A. Shaikh, and M. R. Azimi-Sadjadi are with the Department of Electrical Engineering, Colorado State University, Fort Collins, CO 80523 USA. T. H. Vonder Haar and D. L. Reinke are with the Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University, Fort Collins, CO 80523 USA. Publisher Item Identifier S 1045-9227(99)05313-8. 1 B. Tian, M. A. Shaikh, M. R. Azimi-Sadjadi, T. H. Vonder Haar, and D. L. Reinke, IEEE Trans. Neural Networks, vol. 10, pp. 138–151, Jan. 1999. (a)
منابع مشابه
On the use of Textural Features and Neural Networks for Leaf Recognition
for recognizing various types of plants, so automatic image recognition algorithms can extract to classify plant species and apply these features. Fast and accurate recognition of plants can have a significant impact on biodiversity management and increasing the effectiveness of the studies in this regard. These automatic methods have involved the development of recognition techniques and digi...
متن کاملA study of cloud classification with neural networks using spectral and textural features
The problem of cloud data classification from satellite imagery using neural networks is considered in this paper. Several image transformations such as singular value decomposition (SVD) and wavelet packet (WP) were used to extract the salient spectral and textural features attributed to satellite cloud data in both visible and infrared (IR) channels. In addition, the well-known gray-level coo...
متن کاملA New Method to Improve Automated Classification of Heart Sound Signals: Filter Bank Learning in Convolutional Neural Networks
Introduction: Recent studies have acknowledged the potential of convolutional neural networks (CNNs) in distinguishing healthy and morbid samples by using heart sound analyses. Unfortunately the performance of CNNs is highly dependent on the filtering procedure which is applied to signal in their convolutional layer. The present study aimed to address this problem by a...
متن کاملAn efficient method for cloud detection based on the feature-level fusion of Landsat-8 OLI spectral bands in deep convolutional neural network
Cloud segmentation is a critical pre-processing step for any multi-spectral satellite image application. In particular, disaster-related applications e.g., flood monitoring or rapid damage mapping, which are highly time and data-critical, require methods that produce accurate cloud masks in a short time while being able to adapt to large variations in the target domain (induced by atmospheric c...
متن کامل3D Classification of Urban Features Based on Integration of Structural and Spectral Information from UAV Imagery
Three-dimensional classification of urban features is one of the important tools for urban management and the basis of many analyzes in photogrammetry and remote sensing. Therefore, it is applied in many applications such as planning, urban management and disaster management. In this study, dense point clouds extracted from dense image matching is applied for classification in urban areas. Appl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEEE transactions on neural networks
دوره 10 3 شماره
صفحات -
تاریخ انتشار 1999