Zobrazeno 1 - 10
of 4 569
pro vyhledávání: '"Araghi, A."'
Event cameras offer low-power visual sensing capabilities ideal for edge-device applications. However, their high event rate, driven by high temporal details, can be restrictive in terms of bandwidth and computational resources. In edge AI applicatio
Externí odkaz:
http://arxiv.org/abs/2409.08953
We begin with an exact expression for the entropy of a system of hard spheres within the Hamming space. This entropy relies on probability marginals, which are determined by an extended set of Belief Propagation (BP) equations. The BP probability mar
Externí odkaz:
http://arxiv.org/abs/2409.03670
Autor:
Noohdani, Fahimeh Hosseini, Hosseini, Parsa, Parast, Aryan Yazdan, Araghi, Hamidreza Yaghoubi, Baghshah, Mahdieh Soleymani
Publikováno v:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
While standard Empirical Risk Minimization (ERM) training is proven effective for image classification on in-distribution data, it fails to perform well on out-of-distribution samples. One of the main sources of distribution shift for image classific
Externí odkaz:
http://arxiv.org/abs/2402.18919
Knowledge Distillation (KD) has proven effective for compressing large teacher models into smaller student models. While it is well known that student models can achieve similar accuracies as the teachers, it has also been shown that they nonetheless
Externí odkaz:
http://arxiv.org/abs/2402.03119
Autor:
Ghaznavi, Mahdi, Asadollahzadeh, Hesam, Araghi, HamidReza Yaghoubi, Noohdani, Fahimeh Hosseini, Rohban, Mohammad Hossein, Baghshah, Mahdieh Soleymani
It is well-known that training neural networks for image classification with empirical risk minimization (ERM) makes them vulnerable to relying on spurious attributes instead of causal ones for prediction. Previously, deep feature re-weighting (DFR)
Externí odkaz:
http://arxiv.org/abs/2312.04893
Despite the growing popularity of digital twin (DT) developments, there is a lack of common understanding and definition for important concepts of DT. It is needed to address this gap by building a shared understanding of DT before it becomes an obst
Externí odkaz:
http://arxiv.org/abs/2311.12961
Autor:
Hamid Marashi, Zahra Araghi
Publikováno v:
Research in English Language Pedagogy, Vol 12, Iss 4, Pp 673-697 (2024)
The role and performance of teachers during their classroom interaction are hugely affected by their personality types. Accordingly, the goal of this research was to investigate whether a significant relationship exists between the adversity quotient
Externí odkaz:
https://doaj.org/article/ee7a288cbb754bb0b63926ced4e71244
Autor:
A.C. Pont, M. Parchami-Araghi
Publikováno v:
Кавказский энтомологический бюллетень, Vol 20, Iss 2, Pp 163-180 (2024)
A report is given on two collections of Muscidae (Diptera) from Georgia, made around the village of Kazbegi (now Stepantsminda) in 1983 and on Mount Kudigora (Lagodekhi Reserve) in 2014. A total of 66 species are newly recorded from Georgia, and a ch
Externí odkaz:
https://doaj.org/article/018d7de8268c4420aafdbda25183c459
Autor:
Ardeshir, Hassan, Araghi, Mohammad
One of the common human diseases is sleep disorders. The classification of sleep stages plays a fundamental role in diagnosing sleep disorders, monitoring treatment effectiveness, and understanding the relationship between sleep stages and various he
Externí odkaz:
http://arxiv.org/abs/2309.07182
Autor:
Rostami, Z. Araghi, Niroomand, P.
We categorize all non-abelian nilpotent Lie superalgebras of dimension $(m|n)$, where $1\leq s(L)\leq 10$, and $s(L)$ is a non-negative integer defined by Nayak. Furthermore, we classify the structure of all Lie superalgebras of dimension at most fiv
Externí odkaz:
http://arxiv.org/abs/2309.05415