<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal

Image Fusion Using A Convolutional Neural Network

The study was conducted from November 2021 to May 2022 at the three study sites within the Baghdad governorate. The study aims to identify the impact of human activities on the Tigris River, so an area free of human activities was chosen and represented the first site. A total of 48 types were diagnosed, 6204 ind/m3 spread over three sites. The following environmental indicators were evaluated: Constancy Index (S), Relative abundance index (Ra), Richness Index (between 17.995 and 23.251), Shannon Weiner Index (0.48-1.25 bit/ind.), Uniformity Index (0.124 -0.323). The study showed that the highest percentage recorded was for the phylum Annileda 34%; and the stability index shows that taxes (Stylaria sp., Aoelosoma sp., Branchinra sowerby, Ch

Image   processing   is  an   important   source   for   the  image

analytical    in   order    to    get   variable    parameters    such   as   the

intensity  .In  present   work  it  has  been  found   a  relation   between the  tensity and  number    of  pixd  in  the  image  ,  and  from  this relation   we  have   got   in  this  paper   the  inten

            An image retrieval system is a computer system for browsing, looking and recovering pictures from a huge database of advanced pictures. The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visual and semantic content to a so-called query image. The researchers were developing a new mechanism to retrieval systems which is mainly based on two procedures. The first procedure relies on extract the statistical feature of both original, traditional image by using the histogram and statistical characteristics (mean, standard deviation). The second procedure relies on the T-

Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform w

   This paper determined the difference between the first image of the natural and the second infected image by using logic gates. The proposed algorithm was applied in the first time with binary image, the second time in the gray image, and in the third time in the color image. At start of proposed algorithm the process  images by applying convolution to extended images with zero to obtain more vision and features then enhancements images by Edge detection filter (laplacion operator) and smoothing images by using mean filter ,In order to determine the change between the original image and the injury the logic gates applied specially X-OR gates . Applying the technique for tooth decay through this comparison can locate inj

Due to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.