Zobrazeno 1 - 10
of 17 828
pro vyhledávání: '"Afifi, A."'
Transformers have emerged as a powerful tool for natural language processing (NLP) and computer vision. Through the attention mechanism, these models have exhibited remarkable performance gains when compared to conventional approaches like recurrent
Externí odkaz:
http://arxiv.org/abs/2407.12638
Large language models (LLMs) has been effectively used for many computer vision tasks, including image classification. In this paper, we present a simple yet effective approach for zero-shot image classification using multimodal LLMs. By employing mu
Externí odkaz:
http://arxiv.org/abs/2405.15668
Modern smartphone camera quality heavily relies on the image signal processor (ISP) to enhance captured raw images, utilizing carefully designed modules to produce final output images encoded in a standard color space (e.g., sRGB). Neural-based end-t
Externí odkaz:
http://arxiv.org/abs/2404.10700
In this letter, we address the problem of re-targeting a commercial under-actuated robotic system to a higher dimensional output task. Commercial platforms are equipped with an on-board low-level internal controller that provides the user some virtua
Externí odkaz:
http://arxiv.org/abs/2403.03117
Autor:
Afifi, Mohamed, ElHelw, Mohamed
Perception is a key element for enabling intelligent autonomous navigation. Understanding the semantics of the surrounding environment and accurate vehicle pose estimation are essential capabilities for autonomous vehicles, including self-driving car
Externí odkaz:
http://arxiv.org/abs/2403.03111
High dynamic range (HDR) imaging involves capturing a series of frames of the same scene, each with different exposure settings, to broaden the dynamic range of light. This can be achieved through burst capturing or using staggered HDR sensors that c
Externí odkaz:
http://arxiv.org/abs/2403.02449
Autor:
BOSQUI, TANIA, ABDULRAHIM, SAWSAN, AFIFI, RIMA A., AGER, ALASTAIR, BETANCOURT, THERESA S., CARR, ALAN, HADFIELD, KRISTIN, ISMAIL, GHENA, JORDANS, MARK J.D., JABBOUR, SALAM, KHAZENDAR, ZEENA, MARSHOUD, BASSAM, PUFFER, EVE
Publikováno v:
Health and Human Rights, 2024 Jun 01. 26(1), 147-150.
Externí odkaz:
https://www.jstor.org/stable/48778807
Autor:
Ollero, Anibal, Suarez, Alejandro, Papaioannidis, Christos, Pitas, Ioannis, Marredo, Juan M., Duong, Viet, Ebeid, Emad, Kratky, Vit, Saska, Martin, Hanoune, Chloe, Afifi, Amr, Franchi, Antonio, Vourtsis, Charalampos, Floreano, Dario, Vasiljevic, Goran, Bogdan, Stjepan, Caballero, Alvaro, Ruggiero, Fabio, Lippiello, Vincenzo, Matilla, Carlos, Cioffi, Giovanni, Scaramuzza, Davide, Martinez-de-Dios, Jose R., Arrue, Begona C., Martin, Carlos, Zurad, Krzysztof, Gaitan, Carlos, Rodriguez, Jacob, Munoz, Antonio, Viguria, Antidio
Large-scale infrastructures are prone to deterioration due to age, environmental influences, and heavy usage. Ensuring their safety through regular inspections and maintenance is crucial to prevent incidents that can significantly affect public safet
Externí odkaz:
http://arxiv.org/abs/2401.02343
Publikováno v:
Advances in Electrical and Computer Engineering, Vol 17, Iss 3, Pp 3-10 (2017)
Access to the fine spatial resolution has always been a hotspot in digital imaging. One way to improve resolution is to use signal post-processing techniques. In this study, an improved multi-frame image super-resolution (SR) algorithm is proposed.
Externí odkaz:
https://doaj.org/article/8965bad69f4a45f4afe8d0913ecab8d3
Publikováno v:
Open House International, 2023, Vol. 49, Issue 4, pp. 670-695.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/OHI-06-2023-0146