Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.
Machine learning-based techniques are used widely for the classification of images into various categories. The advancement of Convolutional Neural Network (CNN) affects the field of computer vision on a large scale. It has been applied to classify and localize objects in images. Among the fields of applications of CNN, it has been applied to understand huge unstructured astronomical data being collected every second. Galaxies have diverse and complex shapes and their morphology carries fundamental information about the whole universe. Studying these galaxies has been a tremendous task for the researchers around the world. Researchers have already applied some basic CNN models to predict the morphological classes
... Show MoreIn this paper, the rotation curve of the Milky Way galaxy has been determined using the observed HI emission line at a wavelength of 21 cm. Particularly, the Tangent Point Method was used in order to measure the rotational velocity and the distance to the center of the Milky Way. The measured rotation curve showed that the rotational velocity remains approximately constant at large distances from the center of the Galaxy. This is actually an evidence for the existence of dark matter in the halo of the Milky Way. If all the matter in the Milky Way is visible, then the behavior of the rotation curve of the galaxy should experience a Keplerian decline. The mass of the Milky Way within a radius of 15 kpc was also estimated to be ~ 1.65 × 10
... Show MoreNGC 6946 have been observed with BVRI filters, on October 15-18,
2012, with the Newtonian focus of the 1.88m telescope, Kottamia
observatory, of the National Research Institute of Astronomy and
Geophysics, Egypt (NRIAG), then we combine the BVRI filters to
obtain an astronomical image to the spiral galaxy NGC 6946 which
is regarded main source of information to discover the components of
this galaxy, where galaxies are considered the essential element of
the universe. To know the components of NGC 6946, we studied it
with the Variable Precision Rough Sets technique to determine the
contribution of the Bulge, disk, and arms of NGC 6946 according to
different color in the image. From image we can determined th
Magnetic Resonance Imaging (MRI) is one of the most important diagnostic tool. There are many methods to segment the
tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment the brain with high precision. In this project, the unsupervised classification methods have been used in order to detect the tumor disease from MRI images. These metho
... Show MoreA -set in the projective line is a set of projectively distinct points. From the fundamental theorem over the projective line, all -sets are projectively equivalent. In this research, the inequivalent -sets in have been computed and each -set classified to its -sets where Also, the has been splitting into two distinct -sets, equivalent and inequivalent.
Baghdad University Radio Telescope (BURT) is a 3 meter radio telescope that was installed in the main campus of the University of Baghdad in Jadiriyah. Radio telescopes, in general, offer a wide range of applications in radio astronomy, which are usually used to detect the neutral hydrogen emission line at a wavelength of 21 cm. One of the key applications of BURT is to observe the Milky Way galaxy and to determine its rotation curve. However, performing such observations requires accurate determination of the appropriate observing time as well as the coordinates. This paper focuses on how the observing time and coordinates are calculated correctly and accurately. The horizontal coordinate that corresponds to the galactic coor
... Show MoreTwo galaxies have been chosen, spiral galaxy NGC 5005 and elliptical galaxy NGC 4278 to study their photometric properties by using surface photometric techniques with griz-Filters. Observations are obtained from the Sloan Digital Sky Survey (SDSS). The data reduction of all images have done, like bias and flat field, by SDSS pipeline. The overall structure of the two galaxies (a bulge, a disk), together with isophotal contour maps, surface brightness profiles and a bulge/disk decomposition of the galaxy images were performed, although the disk position angle, ellipticity and inclination of the galaxies have been estimated.
The tasseled cap transformation (TCT) is a useful tool for compressing spectral data into a few bands associated with physical scene characteristics with minimal information loss. TCT was originally evolved from the Landsat multi-spectral scanner (MSS) launched in 1972 and is widely adapted to modern sensors. In this study, we derived the TCT coefficients for operational land imager (OLI) sensor on-board Landsat-8 acquired at 28 Sep.2013. A newly classification method is presented; the method is based on dividing the scatterplot between the Greenness and the Brightness of TCT into regions corresponding to their reflectance values. The results from this paper suggest that the TCT coefficient derived from the OLI bands at September is the
... Show MoreBreast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we
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