The image caption is the process of adding an explicit, coherent description to the contents of the image. This is done by using the latest deep learning techniques, which include computer vision and natural language processing, to understand the contents of the image and give it an appropriate caption. Multiple datasets suitable for many applications have been proposed. The biggest challenge for researchers with natural language processing is that the datasets are incompatible with all languages. The researchers worked on translating the most famous English data sets with Google Translate to understand the content of the images in their mother tongue. In this paper, the proposed review aims to enhance the understanding of image captioning strategies and to survey previous research related to image captioning while examining the most popular databases in different languages, mostly English, translating into other languages using the latest models for describing images, summarizing evaluation measures, and comparing them.
Background: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.
Objective: This study aims to determine the agreement between actual and perceived body image in the general population.
Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10th January 2020 to 21st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass
... Show MoreToday in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,
... Show MoreThe present work aims to study the effect of using an automatic thresholding technique to convert the features edges of the images to binary images in order to split the object from its background, where the features edges of the sampled images obtained from first-order edge detection operators (Roberts, Prewitt and Sobel) and second-order edge detection operators (Laplacian operators). The optimum automatic threshold are calculated using fast Otsu method. The study is applied on a personal image (Roben) and a satellite image to study the compatibility of this procedure with two different kinds of images. The obtained results are discussed.
Background: Prosthodontic services have changed markedly due to an introduction of new materials, techniques and treatment options. The aim of this study were to identify the type of materials and the methods used by dental practitioners in their clinics to construct conventional complete dentures and to specify the type and design for removable partial dentures (RPDs); and to then compare them with those taught in dental schools. Materials and methods: A total of 153 dental practitioners in Sulaimani city completed a written questionnaire. The questionnaire included 19 questions regarding complete and RPDs fabrication. Results: Most of the practitioners provide complete dentures (81.6%) and RPDs (95.3%) in their clinics. Polyvinyl silox
... Show MoreArtificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection
... Show MoreThe article is devoted to the issue of word-formation motivation, which does not lose its relevance and plays a role not only in disclosing formal-semantic relations between words of one language and has not only theoretical, but also applied significance. The authors consider word-formation motivation consistently in its varieties in a comparative way on the materials of so different languages as Russian and Arabic and approach the mechanism of achieving semantic equivalence of translation. To the greatest extent, word-formation activity today, due to objective reasons, affects some special branch (technical, medical, etc.) vocabulary, which is increasing from year to year in national dictionaries. This extensive material, selected
... Show MoreMetaphor is one of the most important linguistic phenomena of the artistic text, as it is the expression of the author’s emotions and evaluations, the result of a deep inner transformation of the semantic words and visual means of reflecting the national culture of each people. This paper examines the concept of linguistic metaphors and analyzes its types in the Russian and Arabic linguistics, provides a comparative analysis of metaphors in Russian and Arabic — all this allows to conclude that metaphorization is characteris- tic of different parts of speech. In the Russian language stylistic differentiation of the metaphors expressed more than in Arabic, so translation of many “sty- listic” metaphors from Russian into Arabic due to
... Show MoreData scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
The bandwidth requirements of telecommunication network users increased rapidly during the last decades. Optical access technologies must provide the bandwidth demand for each user. The passive optical access networks (PONs) support a maximum data rate of 100 Gbps by using the Orthogonal Frequency Division Multiplexing (OFDM) technique in the optical access network. In this paper, the optical broadband access networks with many techniques from Time Division Multiplexing Passive Optical Networks (TDM PON) to Orthogonal Frequency Division Multiplex Passive Optical Networks (OFDM PON) are presented. The architectures, advantages, disadvantages, and main parameters of these optical access networks are discussed and reported which have many ad
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