Zobrazeno 1 - 10
of 304
pro vyhledávání: '"AHMAD, KASHIF"'
In the modern world, our cities and societies face several technological and societal challenges, such as rapid urbanization, global warming & climate change, the digital divide, and social inequalities, increasing the need for more sustainable citie
Externí odkaz:
http://arxiv.org/abs/2412.03600
Autor:
Khan, Naseem, Ahmad, Kashif, Tamimi, Aref Al, Alani, Mohammed M., Bermak, Amine, Khalil, Issa
Industry 5.0, which focuses on human and Artificial Intelligence (AI) collaboration for performing different tasks in manufacturing, involves a higher number of robots, Internet of Things (IoTs) devices and interconnections, Augmented/Virtual Reality
Externí odkaz:
http://arxiv.org/abs/2408.03335
Over the last decade, similar to other application domains, social media content has been proven very effective in disaster informatics. However, due to the unstructured nature of the data, several challenges are associated with disaster analysis in
Externí odkaz:
http://arxiv.org/abs/2405.00903
Autor:
Auyb, Muhammad Asif, Zamir, Muhammad Tayyab, Khan, Imran, Naseem, Hannia, Ahmad, Nasir, Ahmad, Kashif
This paper focuses on a very important societal challenge of water quality analysis. Being one of the key factors in the economic and social development of society, the provision of water and ensuring its quality has always remained one of the top pr
Externí odkaz:
http://arxiv.org/abs/2404.14977
In recent years, the increasing use of Artificial Intelligence based text generation tools has posed new challenges in document provenance, authentication, and authorship detection. However, advancements in stylometry have provided opportunities for
Externí odkaz:
http://arxiv.org/abs/2401.06752
Autor:
Zamir, Muhammad Tayyab, Ayub, Muhammad Asif, Khan, Jebran, Ikram, Muhammad Jawad, Ahmad, Nasir, Ahmad, Kashif
Publikováno v:
IEEE ICAISC 2023
Style analysis, which is relatively a less explored topic, enables several interesting applications. For instance, it allows authors to adjust their writing style to produce a more coherent document in collaboration. Similarly, style analysis can als
Externí odkaz:
http://arxiv.org/abs/2303.01197
Autor:
Suleman, Muhammad, Asif, Muhammad, Zamir, Tayyab, Mehmood, Ayaz, Khan, Jebran, Ahmad, Nasir, Ahmad, Kashif
This paper presents our solutions for the MediaEval 2022 task on DisasterMM. The task is composed of two subtasks, namely (i) Relevance Classification of Twitter Posts (RCTP), and (ii) Location Extraction from Twitter Texts (LETT). The RCTP subtask a
Externí odkaz:
http://arxiv.org/abs/2301.00321
Autor:
Mukhtiar, Wisal, Rizwan, Waliiya, Habib, Aneela, Afridi, Yasir Saleem, Hasan, Laiq, Ahmad, Kashif
In recent years, social media has been widely explored as a potential source of communication and information in disasters and emergency situations. Several interesting works and case studies of disaster analytics exploring different aspects of natur
Externí odkaz:
http://arxiv.org/abs/2301.00320
Autor:
Shoukat, Maria, Ahmad, Khubaib, Said, Naina, Ahmad, Nasir, Hassanuzaman, Mohammed, Ahmad, Kashif
The recent advancement in Multimedia Analytical, Computer Vision (CV), and Artificial Intelligence (AI) algorithms resulted in several interesting tools allowing an automatic analysis and retrieval of multimedia content of users' interests. However,
Externí odkaz:
http://arxiv.org/abs/2207.04762
Metaverse has evolved as one of the popular research agendas that let the users learn, socialize, and collaborate in a networked 3D immersive virtual world. Due to the rich multimedia streaming capability and immersive user experience with high-speed
Externí odkaz:
http://arxiv.org/abs/2207.01512