Zobrazeno 1 - 10
of 2 207
pro vyhledávání: '"A. Esmaeilpour"'
Publikováno v:
Journal of Materials Research and Technology, Vol 18, Iss , Pp 4578-4589 (2022)
The present work focuses on the high temperature flow behavior of additively manufactured 316 L stainless steel. Toward this end, a series of hot compression tests were conducted in the temperature range of 700–1000 °C under the strain rates of 0.
Externí odkaz:
https://doaj.org/article/6f80d5cd891c4ae7b253d3ca30bc0dd2
Autor:
H. jahankhah, A. Esmaeilpour
Publikováno v:
مهندسی عمران شریف, Vol 34.2, Iss 3.2, Pp 59-71 (2018)
Soil-structure interaction is an emerging issue in seismic design of structures. A
Externí odkaz:
https://doaj.org/article/07254c3feabe45ceb3dddf9c688e0848
Autor:
Charandabi, Sina Esmaeilpour
With the growing competition in banking industry, banks are required to follow customer retention strategies while they are trying to increase their market share by acquiring new customers. This study compares the performance of six supervised classi
Externí odkaz:
http://arxiv.org/abs/2301.13099
Autor:
Rezaei, Shahla1 (AUTHOR), Esmaeilpour, Mansour2 (AUTHOR) esmaeilpour@iauh.ac.ir, Hatamlou, Abdolreza3 (AUTHOR), Adabi, Sepideh1 (AUTHOR), Manolakos, Dimitrios E. (AUTHOR) manolako@central.ntua.gr
Publikováno v:
Modelling & Simulation in Engineering. 11/12/2024, Vol. 2024, p1-15. 15p.
This paper introduces a new synthesis-based defense algorithm for counteracting with a varieties of adversarial attacks developed for challenging the performance of the cutting-edge speech-to-text transcription systems. Our algorithm implements a Sob
Externí odkaz:
http://arxiv.org/abs/2207.06858
Autor:
Esmaeilpour, Mohammad, Chaalia, Nourhene, Abusitta, Adel, Devailly, Francois-Xavier, Maazoun, Wissem, Cardinal, Patrick
This paper introduces a novel generative adversarial network (GAN) for synthesizing large-scale tabular databases which contain various features such as continuous, discrete, and binary. Technically, our GAN belongs to the category of class-condition
Externí odkaz:
http://arxiv.org/abs/2205.11693
This paper investigates the impact of different standard environmental sound representations (spectrograms) on the recognition performance and adversarial attack robustness of a victim residual convolutional neural network, namely ResNet-18. Our main
Externí odkaz:
http://arxiv.org/abs/2204.07018
Autor:
Zelič, Klemen, Esmaeilpour, Meysam, Jana, Saibal, Mele, Igor, Wenzel, Wolfgang, Katrašnik, Tomaž
Publikováno v:
In Journal of Power Sources 30 January 2025 627
The primary assumption of conventional supervised learning or classification is that the test samples are drawn from the same distribution as the training samples, which is called closed set learning or classification. In many practical scenarios, th
Externí odkaz:
http://arxiv.org/abs/2203.13238
Existing continual learning techniques focus on either task incremental learning (TIL) or class incremental learning (CIL) problem, but not both. CIL and TIL differ mainly in that the task-id is provided for each test sample during testing for TIL, b
Externí odkaz:
http://arxiv.org/abs/2203.09450