Zobrazeno 1 - 10
of 689
pro vyhledávání: '"A Monsefi"'
Publikováno v:
پژوهشهای زراعی ایران, Vol 22, Iss 2, Pp 137-154 (2024)
IntroductionQuinoa (Chenopodium quinoa L.) is a dicotyledonous, allotetraploid, three-carbon, annual, optional salt-loving plant and is native to South America and the Andean highlands. The growth period of the plant varies between 70 and 240 days de
Externí odkaz:
https://doaj.org/article/9cfbdc952f0d4a1cbaa89aeedd5f8b09
Autor:
Monsefi, Amin Karimi, Shiri, Pouya, Mohammadshirazi, Ahmad, Monsefi, Nastaran Karimi, Davies, Ron, Moosavi, Sobhan, Ramnath, Rajiv
Reducing traffic accidents is a crucial global public safety concern. Accident prediction is key to improving traffic safety, enabling proactive measures to be taken before a crash occurs, and informing safety policies, regulations, and targeted inte
Externí odkaz:
http://arxiv.org/abs/2402.05151
Autor:
Monsefi, Amin Karimi, Karisani, Payam, Zhou, Mengxi, Choi, Stacey, Doble, Nathan, Ji, Heng, Parthasarathy, Srinivasan, Ramnath, Rajiv
Standard modern machine-learning-based imaging methods have faced challenges in medical applications due to the high cost of dataset construction and, thereby, the limited labeled training data available. Additionally, upon deployment, these methods
Externí odkaz:
http://arxiv.org/abs/2402.06190
Autor:
Mohammadshirazi, Ahmad, Nadafian, Aida, Monsefi, Amin Karimi, Rafiei, Mohammad H., Ramnath, Rajiv
Cost-effective sensors are capable of real-time capturing a variety of air quality-related modalities from different pollutant concentrations to indoor/outdoor humidity and temperature. Machine learning (ML) models are capable of performing air-quali
Externí odkaz:
http://arxiv.org/abs/2308.01438
Publikováno v:
in IEEE Signal Processing Letters, vol. 28, pp. 713-717, 2021
Importance sampling (IS) is a powerful Monte Carlo (MC) methodology for approximating integrals, for instance in the context of Bayesian inference. In IS, the samples are simulated from the so-called proposal distribution, and the choice of this prop
Externí odkaz:
http://arxiv.org/abs/2209.13716
Road construction projects maintain transportation infrastructures. These projects range from the short-term (e.g., resurfacing or fixing potholes) to the long-term (e.g., adding a shoulder or building a bridge). Deciding what the next construction p
Externí odkaz:
http://arxiv.org/abs/2209.06813
Lung cancer has been one of the most prevalent disease in recent years. According to the research of this field, more than 200,000 cases are identified each year in the US. Uncontrolled multiplication and growth of the lung cells result in malignant
Externí odkaz:
http://arxiv.org/abs/2201.00227
Autor:
Godaz, Reza, Ghojogh, Benyamin, Hosseini, Reshad, Monsefi, Reza, Karray, Fakhri, Crowley, Mark
Publikováno v:
Proceedings of The 13th Asian Conference on Machine Learning, PMLR, vol. 157, pp. 1-16, 2021
This work concentrates on optimization on Riemannian manifolds. The Limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm is a commonly used quasi-Newton method for numerical optimization in Euclidean spaces. Riemannian LBFGS (RLBFGS) is
Externí odkaz:
http://arxiv.org/abs/2108.11019
Metric learning algorithms aim to learn a distance function that brings the semantically similar data items together and keeps dissimilar ones at a distance. The traditional Mahalanobis distance learning is equivalent to find a linear projection. In
Externí odkaz:
http://arxiv.org/abs/2106.06420
In this paper, we tackle two important problems in low-rank learning, which are partial singular value decomposition and numerical rank estimation of huge matrices. By using the concepts of Krylov subspaces such as Golub-Kahan bidiagonalization (GK-b
Externí odkaz:
http://arxiv.org/abs/2104.10785