Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

      TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work

Background: Body image is one of the most important psychological factors that affects adolescents’ personality and behavior. Body image can be defined as the person’s perceptions, thoughts, and feelings about his or her body.

Objectives: to identify the prevalence of body image concerns among secondary school students and its relation to different factors.

Subjects and methods: A cross-sectional study conducted in which 796 secondary school students participated and body shape concerns was investigated using the body shape questionnaire (BSQ-34).

Results: The prevalence of moderate/marked concern was (21.6%). Moderate/ marked body shape concern was significantly associated

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

The antiviral activity of leaf extracts from Datura stramonium and tomato plants inoculated with TMV, combined with 20% skimmed milk, was investigated. A TMV isolate was confirmed using bioassay, serological, and molecular approaches and subsequently used to inoculate plants. Tomato plants, both pre- and post-inoculated with TMV, were sprayed with leaf extracts from either TMV-free or infected plants, alone or mixed with 20% skimmed milk. Enzyme-linked immunosorbent assay (ELISA) using tobamovirus-specific antibodies and local lesion tests were conducted to assess antiviral activity based on virus concentration and infectivity in treated plants. The experiment followed a completely randomized design (CRD), and the Least Significant

To determine the relationship between Helicobacter pylori infection and Multiple Sclerosis (MS) disorder, 20 patients with MS aged (25-60) years have been investigated from the period of 2016/12/1 to 2017/3/1 and compared to 15 apparently healthy individuals. All study groups were carried out to measure anti H.pylori IgA and H.pylori IgG antibodies by enzyme linked immunosorbent assay (ELISA) technique. There was a significant elevation (p<0.05) in the concentration of anti H.pylori IgG and IgA antibodies (Abs) compared to control group, and there was no significant difference (p>0.05) in the concentration of IgA and IgG (Abs) of H.pylori according to gender, and there was no significant difference (p>0.05) in the concentration of IgA and I

Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.

 Automatic recognition of individuals is very important in modern eras. Biometric techniques have emerged as an answer to the matter of automatic individual recognition. This paper tends to give a technique to detect pupil which is a mixture of easy morphological operations and Hough Transform (HT) is presented in this paper. The circular area of the eye and pupil is divided by the morphological filter as well as the Hough Transform (HT) where the local Iris area has been converted into a rectangular block for the purpose of calculating inconsistencies in the image. This method is implemented and tested on the Chinese Academy of Sciences (CASIA V4) iris image database 249 person and the IIT Delhi (IITD) iris