The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the ac

     The novel coronavirus 2019 (COVID-19) is a respiratory syndrome with similar traits to common pneumonia. This major pandemic has affected nations both socially and economically, disturbing everyday life and urging the scientific community to develop solutions for the diagnosis and prevention of COVID-19. Reverse transcriptase-polymerase chain reaction (RT–PCR) is the conventional approach used for detecting COVID-19. Nevertheless, the initial stage of the infection is less predictable in PCR tests, making early prediction challenging. A robust and alternative diagnostic method based on digital computerised technologies to support conventional methods would greatly help society. Therefore, this paper reviews recent research bas

      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

     Cutaneous leishmaniasis (CL) is an endemic parasitic disease found in many provinces of Iraq. The immune system plays a crucial role in the development or healing of lesions through chemotactic cytokine activity. This study was aimed to detect the levels of two chemokine ligands (CCL2 and CCL5) in Iraqi patients suffering from dermal ulcers, caused by cutaneous leishmaniasis. It was measured in pre and post-treatment state of Pentostam (Pentavalent Antimony 100 mg). Blood serum concentrations of CCL2, CCL5 were measured by enzyme-linked immunosorbent assay among newly infected patients, two-trial treatment patients and three-trial treatment patients, in comparison with the control group. The result indicated a significant differ

In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

    The leading purpose of this work is the development of efficient culture conditions to induce calli from cabbage (Brassica oleracea var. capitata L.) under in vitro conditions. The mature seeds were surface sterilized with combinations of different concentrations of ethanol and NaOCl in different time durations and  were germinated on MS basal medium. The results revealed that the best sterilization method of cabbage seeds was by using 70% ethanol for one minute, followed by 15 min in 2% (NaOCl). Seedlings were used as donor sources for hypocotyls, cotyledon leaves, true leaves, and shoot tip explants. These explants were cultured on different combinations of cytokinins (TDZ, BAP, Ad) an

       The objective of this study is to test In Vitro the twenty chemical compounds that contains Schiff base or oxazepine, indoline, imidazolo units in concentrations( 50, 100, 150) mg / dl as antifungal activity, against three pathogenic Candida species  that occur in humans. We tested one isolates of

   ) Candida albicans ,Candida glabrata and Candida krusei). All these species affect human health . The study was carried out in the Laboratory of Public Health , directly of health for the period from May 2016 to April 2017  , Candida spp isolates used in this study were collected from patients admitted at  some private c