Zobrazeno 1 - 10
of 9 145
pro vyhledávání: '"Aral A"'
Publikováno v:
Demonstratio Mathematica, Vol 57, Iss 1, Pp 246-262 (2024)
In this study, we give a modification of Mellin convolution-type operators. In this way, we obtain the rate of convergence with the modulus of the continuity of the mmth-order Mellin derivative of function ff, but without the derivative of the operat
Externí odkaz:
https://doaj.org/article/77693ab84ce84d8ea7aa4c73f2def6ca
Publikováno v:
Demonstratio Mathematica, Vol 55, Iss 1, Pp 153-162 (2022)
The present paper deals with an extension of approximation properties of generalized sampling series to weighted spaces of functions. A pointwise and uniform convergence theorem for the series is proved for functions belonging to weighted spaces. A r
Externí odkaz:
https://doaj.org/article/e78b8068e2d542e79e898920d0299649
Transformer-based language models are highly effective for code completion, with much research dedicated to enhancing the content of these completions. Despite their effectiveness, these models come with high operational costs and can be intrusive, e
Externí odkaz:
http://arxiv.org/abs/2405.14753
Autor:
Aral, Sinan (AUTHOR) sinana@mit.edu, Brynjolfsson, Erik (AUTHOR) erikb@stanford.edu, Gu, Chris (AUTHOR) chris.gu@scheller.gatech.edu, Hongchang Wang (AUTHOR) hongchang.wang@utdallas.edu, Wu, D. J. (AUTHOR) dj.wu@scheller.gatech.edu
Publikováno v:
MIS Quarterly. Jun2024, Vol. 48 Issue 2, p749-773. 25p. 9 Color Photographs, 1 Diagram, 11 Charts.
Autor:
Ulusoy Gülsüm, Aral Ali
Publikováno v:
Demonstratio Mathematica, Vol 50, Iss 1, Pp 156-174 (2017)
We deal with the approximation properties of a new class of positive linear Durrmeyer type operators which offer a reconstruction of integral type operators including well known Durrmeyer operators. This reconstruction allows us to investigate approx
Externí odkaz:
https://doaj.org/article/58d5f944f26341bbb83230c17ebdeb71
We propose a novel semi-supervised active learning (SSAL) framework for monocular 3D object detection with LiDAR guidance (MonoLiG), which leverages all modalities of collected data during model development. We utilize LiDAR to guide the data selecti
Externí odkaz:
http://arxiv.org/abs/2307.08415
Autor:
Hekimoglu, Aral, Brucker, Adrian, Kayali, Alper Kagan, Schmidt, Michael, Marcos-Ramiro, Alvaro
Curating an informative and representative dataset is essential for enhancing the performance of 2D object detectors. We present a novel active learning sampling strategy that addresses both the informativeness and diversity of the selections. Our st
Externí odkaz:
http://arxiv.org/abs/2307.08414
Autor:
Hekimoglu, Aral, Friedrich, Philipp, Zimmer, Walter, Schmidt, Michael, Marcos-Ramiro, Alvaro, Knoll, Alois C.
Learning-based solutions for vision tasks require a large amount of labeled training data to ensure their performance and reliability. In single-task vision-based settings, inconsistency-based active learning has proven to be effective in selecting i
Externí odkaz:
http://arxiv.org/abs/2306.12398
Autor:
ARAL, BERDAL
Publikováno v:
Insight Turkey, 2023 Oct 01. 25(4), 181-196.
Externí odkaz:
https://www.jstor.org/stable/48754800
Autor:
KELEŞ, Elif1,2, ARAL, Arzu3,4 arzu.aral@gmail.com, ELMAZOĞLU, Zübeyir5, KAZAN, Hasan Hüseyin6, ABBASOĞLU TOPA, Elif Gülçiçek1,3, ERGÜN, Mehmet Ali7, BOLAY, Hayrunnisa1,3,8
Publikováno v:
Turkish Journal of Medical Sciences. 2024, Vol. 54 Issue 5, p1102-1115. 14p.