Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Sun, Jinyuan Stella"'
The future of transportation is being shaped by technology, and one revolutionary step in improving road safety is the incorporation of robotic systems into driver monitoring infrastructure. This literature review explores the current landscape of dr
Externí odkaz:
http://arxiv.org/abs/2401.15762
Autor:
Riya, Farhin Farhad, Hoque, Shahinul, Onim, Md Saif Hassan, Michaud, Edward, Begoli, Edmon, Sun, Jinyuan Stella
The widespread adoption of Image Processing has propelled Object Recognition (OR) models into essential roles across various applications, demonstrating the power of AI and enabling crucial services. Among the applications, traffic sign recognition s
Externí odkaz:
http://arxiv.org/abs/2305.05499
In the power system, security assessment (SA) plays a pivotal role in determining the safe operation in a normal situation and some contingencies scenarios. Electrical variables as input variables of the model are mainly considered to indicate the po
Externí odkaz:
http://arxiv.org/abs/2301.12988
Deep Neural Networks have proven to be highly accurate at a variety of tasks in recent years. The benefits of Deep Neural Networks have also been embraced in power grids to detect False Data Injection Attacks (FDIA) while conducting critical tasks li
Externí odkaz:
http://arxiv.org/abs/2301.12487
Short-term load forecasting is an essential task that supports utilities to schedule generating sufficient power for balancing supply and demand, and can become an attractive target for cyber attacks. It has been shown that the power system state est
Externí odkaz:
http://arxiv.org/abs/2203.03774
False data injection attacks (FDIAs) pose a significant security threat to power system state estimation. To detect such attacks, recent studies have proposed machine learning (ML) techniques, particularly deep neural networks (DNNs). However, most o
Externí odkaz:
http://arxiv.org/abs/2102.09057
Effective detection of energy theft can prevent revenue losses of utility companies and is also important for smart grid security. In recent years, enabled by the massive fine-grained smart meter data, deep learning (DL) approaches are becoming popul
Externí odkaz:
http://arxiv.org/abs/2010.09212
Energy theft causes large economic losses to utility companies around the world. In recent years, energy theft detection approaches based on machine learning (ML) techniques, especially neural networks, become popular in the research literature and a
Externí odkaz:
http://arxiv.org/abs/2006.03504
Recent research demonstrated that the superficially well-trained machine learning (ML) models are highly vulnerable to adversarial examples. As ML techniques are becoming a popular solution for cyber-physical systems (CPSs) applications in research l
Externí odkaz:
http://arxiv.org/abs/2003.05631
Outsourcing data storage to the remote cloud can be an economical solution to enhance data management in the smart grid ecosystem. To protect the privacy of data, the utility company may choose to encrypt the data before uploading them to the cloud.
Externí odkaz:
http://arxiv.org/abs/1808.00645