A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2

يعد التقطيع الصوري من الاهداف الرئيسة والضرورية في المعالجات الصورية للصور الرقمية، فهو يسعى الى تجزئة الصور المدروسة الى مناطق متعددة اكثر نفعاً تلخص فيها المناطق ذات الافادة لصور الاقمار الصناعية، وهي صور متعددة الاطياف ومجهزة من الاقمار الصناعية باستخدام مبدأ الاستشعار عن بعد والذي اصبح من المفاهيم المهمة التي تُعتمد تطبيقاته في اغلب ضروريات الحياة اليومية، وخاصة بعد التطورات المتسارعة التي شهد

     Numerical simulations were carried out to evaluate the effects of different aberrations modes on the performance of optical system, when observing and imaging the solar surface. Karhunen-Loeve aberrations modes were simulated as a wave front error in the aperture function of the optical system. To identify and apply the appropriate rectification that removes or reduces various types of aberration, their attribute must be firstly determined and quantitatively described. Wave aberration function is well suitable for this purpose because it fully characterizes the progressive effect of the optical system on the wave front passing through the aperture. The Karhunen-Loeve polynomials for circular aperture were used to

Background: The present study was carried out to compare shear bond strength of sapphire bracket bonded to zirconium surface after using different methods of surface conditioning and assessment of the adhesive remnant index. Materials and methods: The sample composed of 40 zirconium specimens divided into four groups; the first group was the control, the second group was conditioned by sandblast with aluminum oxide particle 50 μm, the third and fourth group was treated by (Nd: YAG) laser (1064nm)(0.888 Watt for 5 seconds) for the 1st laser group and (0.444 Watt for 10 seconds) for the 2nd laser group. All samples were coated by z-prime plus primer. A central incisor sapphire bracket was bonded to all samples with light cure adhesive res

Statistical fluctuations of nuclear energy spectra for the isobar A = 68 were examined by means of the random matrix theory together with the nuclear shell model. The isobar A = 68 nuclei are suggested to consist of an inert core of ⁵⁶Ni with 12 nucleons in f5p-space (2p_3/2, 1f_5/2 and 2p_1/2 orbitals). The nuclear excitation energies, required by this work, were obtained through performing f5p-shell model calculations using the isospin formalism f5pvh interaction with realistic single particle energies. All calculations of the present study were conducted using the OXBASH code. The calculated level densities were found to have a Gaussian shape. The distributions of level spacing P(s) an

In this paper, we made comparison among different parametric ,nonparametric and semiparametric estimators for partial linear regression model users parametric represented by ols and nonparametric methods represented by cubic smoothing spline estimator and Nadaraya-Watson estimator, we study three nonparametric regression models and samples sizes  n=40,60,100,variances used σ²=0.5,1,1.5 the results  for the first model show that N.W estimator for partial linear regression model(PLM) is the best followed the cubic smoothing spline estimator for (PLM),and the results of the second and the third model show that the best estimator is C.S.S.followed by N.W estimator for (PLM) ,the

     Always MRI and CT Medical images are noisy so that preprocessing is necessary for enhance these images to assist clinicians and make accurate diagnosis. Firstly, in the proposed method uses two denoising filters (Median and Slantlet) are applied to images in parallel and the best enhanced image gained from both filters is voted by use PSNR and MSE as image quality measurements. Next, extraction of brain tumor from cleaned images is done by segmentation method based on k-mean.  The result shows that the proposed method is giving an optimal solution due to denoising method which is based on multiple filter types to obtain best clear images and that is leads to make the extraction of tumor more precision best.<

In this paper ,the problem of point estimation for the two parameters of logistic distribution has been investigated using simulation technique. The rank sampling set estimator method which is one of the Non_Baysian procedure and Lindley approximation estimator method which is one of the Baysian method were used to estimate the parameters of logistic distribution. Comparing between these two mentioned methods by employing mean square error measure and mean absolute percentage error measure .At last simulation technique used to generate many number of samples sizes to compare between these methods.