Zobrazeno 1 - 10
of 65 853
pro vyhledávání: '"Rezvani, A"'
Autor:
HAAKE, GREGORY
Publikováno v:
Renaissance and Reformation / Renaissance et Réforme, 2022 Oct 01. 45(4), 229-231.
Externí odkaz:
https://www.jstor.org/stable/27245425
Autor:
Lojewski, Tobias, Guyader, Loïc Le, Agarwal, Naman, Boeglin, Christine, Carley, Robert, Castoldi, Andrea, Deiter, Carsten, Engel, Robin Y., Erdinger, Florian, Fangohr, Hans, Fiorini, Carlo, Gerasimova, Natalia, Gort, Rafael, de Groot, Frank, Hansen, Karsten, Hauf, Steffen, Hickin, David, Izquierdo, Manuel, Kämmerer, Lea, Van Kuiken, Benjamin E., Lomidze, David, Maffessanti, Stefano, Mercadier, Laurent, Mercurio, Giuseppe, Miedema, Piter S., Pace, Matthias, Porro, Matteo, Rezvani, Javad, Rothenbach, Nico, Rösner, Benedikt, Samartsev, Andrey, Schlappa, Justina, Stamm, Christian, Teichmann, Martin, Turcato, Monica, Yaroslavtsev, Alexander, Döring, Florian, Scherz, Andreas, David, Christian, Beye, Martin, Bovensiepen, Uwe, Wende, Heiko, Eschenlohr, Andrea, Ollefs, Katharina
Time-resolved X-ray absorption spectroscopy (tr-XAS) has been shown to be a versatile measurement technique for investigating non-equilibrium dynamics. Novel X-ray free electron laser (XFEL) facilities like the European XFEL offer increased repetitio
Externí odkaz:
http://arxiv.org/abs/2412.05151
FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation
Early detection of lung cancer is crucial as it increases the chances of successful treatment. Automatic lung image segmentation assists doctors in identifying diseases such as lung cancer, COVID-19, and respiratory disorders. However, lung segmentat
Externí odkaz:
http://arxiv.org/abs/2410.15812
Autor:
Rezvani, Hadi, Zarrabi, Navid, Mehta, Ishaan, Kolios, Christopher, Jaafar, Hussein Ali, Kao, Cheng-Hao, Saeedi, Sajad, Yousefi, Nariman
Plastic pollution presents an escalating global issue, impacting health and environmental systems, with micro- and nanoplastics found across mediums from potable water to air. Traditional methods for studying these contaminants are labor-intensive an
Externí odkaz:
http://arxiv.org/abs/2409.13688
Autor:
Huang, Wenjun, Ni, Yang, Rezvani, Arghavan, Jeong, SungHeon, Chen, Hanning, Liu, Yezi, Wen, Fei, Imani, Mohsen
Human pose estimation (HPE) is crucial for various applications. However, deploying HPE algorithms in surveillance contexts raises significant privacy concerns due to the potential leakage of sensitive personal information (SPI) such as facial featur
Externí odkaz:
http://arxiv.org/abs/2409.02715
Uplink Wave-Domain Combiner for Stacked Intelligent Metasurfaces Accounting for Hardware Limitations
Refractive metasurfaces (RMTSs) offer a promising solution to improve energy efficiency of wireless systems. To address the limitations of single-layer RMTS, stacked intelligent metasurfaces (SIMs), which form the desired precoder and combiner in the
Externí odkaz:
http://arxiv.org/abs/2407.21012
Dynamic Metasurface Antennas (DMAs) have emerged as promising candidates for basestation deployment in the next generation of wireless communications. While overlooking the practical and hardware limitations of DMA, previous studies have highlighted
Externí odkaz:
http://arxiv.org/abs/2407.20988
This paper presents a review on methods for class-imbalanced learning with the Support Vector Machine (SVM) and its variants. We first explain the structure of SVM and its variants and discuss their inefficiency in learning with class-imbalanced data
Externí odkaz:
http://arxiv.org/abs/2406.03398
Autor:
Huang, Wenjun, Chen, Hanning, Ni, Yang, Rezvani, Arghavan, Yun, Sanggeon, Jeon, Sungheon, Pedley, Eric, Imani, Mohsen
Detecting marine objects inshore presents challenges owing to algorithmic intricacies and complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative sensing system that splits the task into object localization and fine-
Externí odkaz:
http://arxiv.org/abs/2403.14027
Autor:
Heydari, Mohammad, Rezvani, Zahra
Data is becoming more complex, and so are the approaches designed to process it. Enterprises have access to more data than ever, but many still struggle to glean the full potential of insights from what they have. This research explores the challenge
Externí odkaz:
http://arxiv.org/abs/2402.12281