IEEE Galveston Bay Section

In today's dynamic and interconnected world, the pace of change is accelerating at an unprecedented rate. As our systems and technologies become increasingly intelligent and automated, we are presented with new opportunities and challenges. The growing interconnectivity in every aspect of life has undoubtedly enhanced convenience and efficiency, but it has also introduced vulnerabilities, paving the way for emerging cyber threats. This seminar aims to explore the pressing need for automation and intelligence in our security systems to effectively combat the ever-evolving threat landscape. We will delve into a cutting-edge solution – an autonomous security system capable of not only identifying new, previously unseen threats but also autonomously learning from them without any human intervention. The key focus of this seminar will be on the concept of incremental learning and the open world recognition problem. We will discuss how this innovative security system addresses these challenges. By adapting to new threats as they emerge and continuously updating its knowledge base, this autonomous system ensures that it remains vigilant and capable of defending against even the most sophisticated and novel attacks. Virtual: https://events.vtools.ieee.org/m/380837

In today's dynamic and interconnected world, the pace of change is accelerating at an unprecedented rate. As our systems and technologies become increasingly intelligent and automated, we are presented with new opportunities and challenges. The growing interconnectivity in every aspect of life has undoubtedly enhanced convenience and efficiency, but it has also introduced vulnerabilities, paving the way for emerging cyber threats. This seminar aims to explore the pressing need for automation and intelligence in our security systems to effectively combat the ever-evolving threat landscape. We will delve into a cutting-edge solution – an autonomous security system capable of not only identifying new, previously unseen threats but also autonomously learning from them without any human intervention. The key focus of this seminar will be on the concept of incremental learning and the open world recognition problem. We will discuss how this innovative security system addresses these challenges. By adapting to new threats as they emerge and continuously updating its knowledge base, this autonomous system ensures that it remains vigilant and capable of defending against even the most sophisticated and novel attacks. Co-sponsored by: MUHAMMAD USMAN ASAD Speaker(s): IRFAN, Virtual: https://events.vtools.ieee.org/m/376288

More than 80% of consumer Internet traffic is for videos and most of them are recorded videos. Meanwhile, many organizations (such as national parks, vacation resorts, and departments of transportation) provide real-time visual data (images or videos). These videos allow Internet users to observe events remotely. This speech explains how to discover real-time visual data on the Internet. The discovery process uses a crawler to reach many web pages. The information on these web pages is analyzed to identify candidates of real-time data. The data is downloaded multiple times over an extended time period; changes are detected to determine whether it is likely to provide real-time data. The data can be used during an emergency. For example, viewers may check whether a street is flooded and cannot pass. It is also possible to use the data to observe long-term trends, such as how people react to movement restrictions during the COVID pandemic. Speaker(s): DR LU, Virtual: https://events.vtools.ieee.org/m/382713