Zobrazeno 1 - 10
of 20 693
pro vyhledávání: '"Zeid IF"'
Foundation deep learning (DL) models are general models, designed to learn general, robust and adaptable representations of their target modality, enabling finetuning across a range of downstream tasks. These models are pretrained on large, unlabeled
Externí odkaz:
http://arxiv.org/abs/2411.09996
Foundational deep learning (DL) models are general models, trained on large, diverse, and unlabelled datasets, typically using self-supervised learning techniques have led to significant advancements especially in natural language processing. These p
Externí odkaz:
http://arxiv.org/abs/2411.09849
Autor:
Garcia, Gonzalo Martin, Zeid, Karim Abou, Schmidt, Christian, de Geus, Daan, Hermans, Alexander, Leibe, Bastian
Recent work showed that large diffusion models can be reused as highly precise monocular depth estimators by casting depth estimation as an image-conditional image generation task. While the proposed model achieved state-of-the-art results, high comp
Externí odkaz:
http://arxiv.org/abs/2409.11355
Foundational Large Language Models (LLMs) such as GPT-3.5-turbo allow users to refine the model based on newer information, known as ``fine-tuning''. This paper leverages this ability to analyze AC-DC converter behaviors, focusing on the ripple curre
Externí odkaz:
http://arxiv.org/abs/2407.01724
Autor:
Nahass, George R., Kaplan, Nicolas, Scharf, Isabel, Saini, Devansh, Zeid, Naji Bou, Kazmouz, Sobhi, Zhao, Linping, Alkureishi, Lee W. T.
The fibula-free flap (FFF) is a valuable reconstructive technique in maxillofacial surgery; however, the assessment of osteotomy accuracy remains challenging. We devised two novel methodologies to compare planned and postoperative osteotomies in FFF
Externí odkaz:
http://arxiv.org/abs/2406.02824
Autor:
Fan, Zicong, Ohkawa, Takehiko, Yang, Linlin, Lin, Nie, Zhou, Zhishan, Zhou, Shihao, Liang, Jiajun, Gao, Zhong, Zhang, Xuanyang, Zhang, Xue, Li, Fei, Liu, Zheng, Lu, Feng, Zeid, Karim Abou, Leibe, Bastian, On, Jeongwan, Baek, Seungryul, Prakash, Aditya, Gupta, Saurabh, He, Kun, Sato, Yoichi, Hilliges, Otmar, Chang, Hyung Jin, Yao, Angela
We interact with the world with our hands and see it through our own (egocentric) perspective. A holistic 3Dunderstanding of such interactions from egocentric views is important for tasks in robotics, AR/VR, action recognition and motion generation.
Externí odkaz:
http://arxiv.org/abs/2403.16428
The industrial Internet of Things (IIoT) under Industry 4.0 heralds an era of interconnected smart devices where data-driven insights and machine learning (ML) fuse to revolutionize manufacturing. A noteworthy development in IIoT is the integration o
Externí odkaz:
http://arxiv.org/abs/2403.14120
Autor:
Allouche, Mohammad, Sevostianov, Vladislav I., Zahn, Einara, Zondlo, Mark, Dias, Nelson Luís, Katul, Gabriel G., Fuentes, Jose D., Bou-Zeid, Elie
Conventional and recently developed approaches for estimating turbulent scalar fluxes under stable conditions are evaluated. The focus is on methods that do not require fast scalar sensors such as the relaxed eddy accumulation (REA) approach, the dis
Externí odkaz:
http://arxiv.org/abs/2401.11756
Unsteady land-sea breezes (LSBs) resulting from time-varying surface thermal contrasts are explored in the presence of a constant synoptic pressure forcing, Mg, when the latter is oriented from sea to land versus land to sea. Large eddy simulations r
Externí odkaz:
http://arxiv.org/abs/2401.00863
Ensuring adequate ventilation of exterior and interior urban spaces is essential for the safety and comfort of inhabitants. Here, we examine how angled features can steer wind into areas with stagnant air, promoting natural ventilation. Using Large E
Externí odkaz:
http://arxiv.org/abs/2310.01577