Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Aved, Alexander"'
Publikováno v:
the IEEE IT Professional, Special Issue on Information Hygiene and the Fight against the Misinformation Info-demic, 2022
Advancements in generative models, like Deepfake allows users to imitate a targeted person and manipulate online interactions. It has been recognized that disinformation may cause disturbance in society and ruin the foundation of trust. This article
Externí odkaz:
http://arxiv.org/abs/2207.13070
Advancement in artificial intelligence (AI) and machine learning (ML), dynamic data driven application systems (DDDAS), and hierarchical cloud-fog-edge computing paradigm provide opportunities for enhancing multi-domain systems performance. As one ex
Externí odkaz:
http://arxiv.org/abs/2004.10674
Situation AWareness (SAW) is essential for many mission critical applications. However, SAW is very challenging when trying to immediately identify objects of interest or zoom in on suspicious activities from thousands of video frames. This work aims
Externí odkaz:
http://arxiv.org/abs/2003.04169
Urban imagery usually serves as forensic analysis and by design is available for incident mitigation. As more imagery collected, it is harder to narrow down to certain frames among thousands of video clips to a specific incident. A real-time, proacti
Externí odkaz:
http://arxiv.org/abs/1909.05776
Edge computing provides the ability to link distributor users for multimedia content, while retaining the power of significant data storage and access at a centralized computer. Two requirements of significance include: what information show be proce
Externí odkaz:
http://arxiv.org/abs/1807.11329
Information from surveillance video is essential for situational awareness (SAW). Nowadays, a prohibitively large amount of surveillance data is being generated continuously by ubiquitously distributed video sensors. It is very challenging to immedia
Externí odkaz:
http://arxiv.org/abs/1807.06179
Publikováno v:
ICIP 2018
Superpixel-based Higher-order Conditional Random Fields (CRFs) are effective in enforcing long-range consistency in pixel-wise labeling problems, such as semantic segmentation. However, their major short coming is considerably longer time to learn hi
Externí odkaz:
http://arxiv.org/abs/1805.11737
Superpixel-based Higher-order Conditional random fields (SP-HO-CRFs) are known for their effectiveness in enforcing both short and long spatial contiguity for pixelwise labelling in computer vision. However, their higher-order potentials are usually
Externí odkaz:
http://arxiv.org/abs/1804.02032
Publikováno v:
Journal of Cybersecurity & Privacy; Jun2024, Vol. 4 Issue 2, p223-240, 18p
Autor:
Munir, Arslan1 (AUTHOR) amunir@ksu.edu, Aved, Alexander2 (AUTHOR) Alexander.Aved@us.af.mil, Blasch, Erik3 (AUTHOR) erik.blasch.1@us.af.mil
Publikováno v:
AI. Mar2022, Vol. 3 Issue 1, p55-77. 23p.