IOT control and surveillance system
An automated system is a combination of both software and hardware which is designed and programmed to work automatically without the need of any human operator to provide inputs and instructions for each operation. The Internet of Things (IoT) is a network of connected things. These ‘things’ (devices) communicate with each other using machine to machine communication (M2M). Information is traversed between devices so that processes can be automated, without the need for human intervention. By reducing the number of people involved in a business process, several advantages arise, including improved accuracy and up-time. We will build an IoT automated system to control access of humans and vehicles to a warehouse based on biometrics and image recognition techniques.
Interactive drink machine company - (IDM company)
This project is a continuation of our previous project for a hot drink machine by adding the capability for electronic payment and developing the company's management system and making the hot drink machine linkable with the company's server via the Internet and more interactive with the customer through the development of this project according to several aspects. On the software level: An integrated system that allows recording customer requests and executed operations, in addition to information about users, including their personal information, current balance, and executed requests. On the level of employees, their personal information, their work tasks and the operations carried out by them (Receipt and delivery of materials and servicing of machines).
Hydra = هايدرا
Forgery involves the use of advanced algorithms to replicate and distribute deceptive products across various categories, casting shadows of doubt on the authenticity of goods. Although counterfeit detection can be useful in identifying and mitigating fraudulent activities, the widespread presence of counterfeit goods poses significant dangers, undermining consumer confidence and brand reputation. To underscore the severity of this issue, consider instances such as fake luxury items flooding the market, counterfeit electronics compromising safety, or bogus pharmaceuticals endangering health. Addressing this issue is critical in maintaining the integrity of brands, safeguarding consumer well-being, and preserving trust in the marketplace. The ability to distinguish between authentic and counterfeit products is paramount in ensuring accurate decision-making and preventing the harmful consequences of fraudulent goods. This technological context underscores the urgency of developing and deploying cutting-edge solutions to combat the evolving landscape of product forgery. Hydra emerges as a robust solution, utilizing a comprehensive approach that includes extracting posts and images from search engine tools, and is integrated with AI models to detect forgery. The Hydra platform not only provides users with a powerful tool for detecting counterfeit products but also offers tangible benefits such as enhanced brand security, increased awareness about the prevalence of forgeries, and the opportunity to actively participate in a real-time community.
Deepfake detection
Recently, various techniques of manipulating the video content have become available to everyone – online, one can find free applications e.g., for face swapping in videos. Such universal accessibility carries a notable risk of flooding online content with false information, affecting not only the greats of this world, but also the whole societies, also the rapid progress in synthetic image generation and manipulation has now come to a point where it raises significant concerns for the implications towards society. It is therefore necessary to develop a verification tool that will help assess the authenticity of the videos posted on the internet. This project describes the approach of using artificial intelligence solutions to detect doctored videos.
Machine Intelligence and Big Data Analytics for Cybersecurity Applications
Presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field.
Automatic video editor
Searching in a large database of videos is one of the challenges faced by the user today as most of the results are inaccurate or correct. In our project, we worked on developing a system that receives the search word from the user and searches for it among a large number of videos using MSR-VTT dataset and COCO data set based on the elements that we see inside the video. Entered by the user. We have also worked on adding other options that the user can benefit from in modifying the videos, such as entering a black and white video clip and returning the result in color. The user can also enter a low-resolution video clip, and the system improves the accuracy of the video and sends it.
Advances in Multilingual and Multimodal Information Retrieval ; 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers
This book constitutes the thoroughly refereed proceedings of the 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, held in Budapest, Hungary, September 2007.






