Zobrazeno 1 - 10
of 8 074
pro vyhledávání: '"RAZZAK, A."'
Autor:
Rehman, Abd Ur, Rehman, Azka, Usman, Muhammad, Shahid, Abdullah, Gho, Sung-Min, Lee, Aleum, Khan, Tariq M., Razzak, Imran
Brain aging involves structural and functional changes and therefore serves as a key biomarker for brain health. Combining structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI) has the potential to improve brai
Externí odkaz:
http://arxiv.org/abs/2412.05632
Autor:
Althubyani, Mohammed, Meng, Zhijin, Xie, Shengyuan, Seung, Cha, Razzak, Imran, Sandoval, Eduardo Benitez, Kocaballi, Baki, Bamdad, Mahdi, Naranjo, Francisco Cruz
The integration of conversational agents into our daily lives has become increasingly common, yet many of these agents cannot engage in deep interactions with humans. Despite this, there is a noticeable shortage of datasets that capture multimodal in
Externí odkaz:
http://arxiv.org/abs/2412.04908
Reuse distance analysis is a widely recognized method for application characterization that illustrates cache locality. Although there are various techniques to calculate the reuse profile from dynamic memory traces, it is both time and space-consumi
Externí odkaz:
http://arxiv.org/abs/2411.13854
Autor:
Xie, Tong, Zhang, Hanzhi, Wang, Shaozhou, Wan, Yuwei, Razzak, Imran, Kit, Chunyu, Zhang, Wenjie, Hoex, Bram
Natural Language Processing (NLP) is widely used to supply summarization ability from long context to structured information. However, extracting structured knowledge from scientific text by NLP models remains a challenge because of its domain-specif
Externí odkaz:
http://arxiv.org/abs/2411.12000
Autor:
Usman, Muhammad, Rehman, Azka, Shahid, Abdullah, Rehman, Abd Ur, Gho, Sung-Min, Lee, Aleum, Khan, Tariq M., Razzak, Imran
Despite advances in deep learning for estimating brain age from structural MRI data, incorporating functional MRI data is challenging due to its complex structure and the noisy nature of functional connectivity measurements. To address this, we prese
Externí odkaz:
http://arxiv.org/abs/2411.10100
Autor:
Chatterjee, Soumick, Mattern, Hendrik, Dörner, Marc, Sciarra, Alessandro, Dubost, Florian, Schnurre, Hannes, Khatun, Rupali, Yu, Chun-Chih, Hsieh, Tsung-Lin, Tsai, Yi-Shan, Fang, Yi-Zeng, Yang, Yung-Ching, Huang, Juinn-Dar, Xu, Marshall, Liu, Siyu, Ribeiro, Fernanda L., Bollmann, Saskia, Chintalapati, Karthikesh Varma, Radhakrishna, Chethan Mysuru, Kumara, Sri Chandana Hudukula Ram, Sutrave, Raviteja, Qayyum, Abdul, Mazher, Moona, Razzak, Imran, Rodero, Cristobal, Niederren, Steven, Lin, Fengming, Xia, Yan, Wang, Jiacheng, Qiu, Riyu, Wang, Liansheng, Panah, Arya Yazdan, Jurdi, Rosana El, Fu, Guanghui, Arslan, Janan, Vaillant, Ghislain, Valabregue, Romain, Dormont, Didier, Stankoff, Bruno, Colliot, Olivier, Vargas, Luisa, Chacón, Isai Daniel, Pitsiorlas, Ioannis, Arbeláez, Pablo, Zuluaga, Maria A., Schreiber, Stefanie, Speck, Oliver, Nürnberger, Andreas
The human brain receives nutrients and oxygen through an intricate network of blood vessels. Pathology affecting small vessels, at the mesoscopic scale, represents a critical vulnerability within the cerebral blood supply and can lead to severe condi
Externí odkaz:
http://arxiv.org/abs/2411.09593
Visual Question Answering (VQA) has emerged as a promising area of research to develop AI-based systems for enabling interactive and immersive learning. Numerous VQA datasets have been introduced to facilitate various tasks, such as answering questio
Externí odkaz:
http://arxiv.org/abs/2410.22648
Autor:
Lin, Xiachong, Prabowo, Arian, Razzak, Imran, Xue, Hao, Amos, Matthew, Behrens, Sam, Salim, Flora D.
The growing integration of digitized infrastructure with Internet of Things (IoT) networks has transformed the management and optimization of building energy consumption. By leveraging IoT-based monitoring systems, stakeholders such as building manag
Externí odkaz:
http://arxiv.org/abs/2411.08888
Large Language Models (LLMs) are known to hallucinate, whereby they generate plausible but inaccurate text. This phenomenon poses significant risks in critical applications, such as medicine or law, necessitating robust hallucination mitigation strat
Externí odkaz:
http://arxiv.org/abs/2410.17234
Large Language Models (LLMs) are trained on massive amounts of data, enabling their application across diverse domains and tasks. Despite their remarkable performance, most LLMs are developed and evaluated primarily in English. Recently, a few multi-
Externí odkaz:
http://arxiv.org/abs/2410.13153