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 media. Our investigation rigorously assesses the capabilities of these advanced LLMs in identifying and differentiating manipulated imagery. We explore how these models process visual data, their effectiveness in recognizing subtle alterations, and their potential in safeguarding against misleading representations. The implications of our findings are far-reaching, impacting areas such as security, media integrity, and the trustworthiness of information in digital platforms. Moreover, the study sheds light on the limitations and strengths of current LLMs in handling complex tasks like image verification, thereby contributing valuable insights to the ongoing discourse on AI ethics and digital media reliability.
Wireless networks and communications have witnessed tremendous development and growth in recent periods and up until now, as there is a group of diverse networks such as the well-known wireless communication networks and others that are not linked to an infrastructure such as telephone networks, sensors and wireless networks, especially in important applications that work to send and receive important data and information in relatively unsafe environments, cybersecurity technologies pose an important challenge in protecting unsafe networks in terms of their impact on reducing crime. Detecting hacking in electronic networks and penetration testing. Therefore, these environments must be monitored and protected from hacking and malicio
... Show More'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
Media plays an important role in shaping the mental image of their audiences for individuals, groups and organizations, States and peoples. It is the window through which overlooks the masses on events and issues, and in the light of their exposure to these means are their opinions and impressions.
Despite the importance of direct experiences in shaping opinions, drawing pictures and impressions, it is inevitable to rely on these means as individuals can not engage in direct experiences with thousands of events, issues and topics that concern their community and other societies.
There is no doubt that media is of great importance at the present time, because of its significant impact in the management of the course of pol
... Show MoreStructure type and disorder have become important questions in catalyst design, with the most active catalysts often noted to be “disordered” or “amorphous” in nature. To quantify the effects of disorder and structure type systematically, a test set of manganese(III,IV) oxides was developed and their reactivity as oxidants and catalysts tested against three substrates: methylene blue, hydrogen peroxide, and water. We find that disorder destabilizes the materialsthermodynamically, making them stronger chemical oxidantsbut not necessarily better catalysts. For the disproportionation of H2O2 and the oxidative decomposition of methylene blue, MnOx-mediated direct oxidation competes with catalytically mediated oxidation, making the most
... Show MoreThis research including lineament automated extraction by using PCI Geomatica program, depending on satellite image and lineament analysis by using GIS program. Analysis included density analysis, length density analysis and intersection density analysis. When calculate the slope map for the study area, found the relationship between the slope and lineament density.
The lineament density increases in the regions that have high values for the slope, show that lineament play an important role in the classification process as it isolates the class for the other were observed in Iranian territory, clearly, also show that one of the lineament hit shoulders of Galal Badra dam and the surrounding areas dam. So should take into consideration
Maintaining the quality of apricot fruits during storage is not an easy task due to the changes in their physical and chemical properties, so it is necessary to use less expensive, easy to apply, environmentally friendly, and safer preservatives to maintain the nutritional value of apricot. The damage to some fruits during storage can be a source of infection, which leads to the damage of healthy fruits more quickly, which requires building an intelligent model to detect damaged fruits. The aim of the research is to study the effect of immersing apricots in lemon juice once and sugar-water solution again on the quality properties of apricots, including sweetness, color, hardness, and water content. On the other hand, the YOLOv7 algorithm wa
... Show MoreConvolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
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