Výsledky vyhledávání - "RAHMAN, MD. ATIQUR"

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FUSED-Net: Enhancing Few-Shot Traffic Sign Detection with Unfrozen Parameters, Pseudo-Support Sets, Embedding Normalization, and Domain Adaptation

Autor: Rahman, Md. Atiqur, Asad, Nahian Ibn, Omi, Md. Mushfiqul Haque, Hasan, Md. Bakhtiar, Ahmed, Sabbir, Kabir, Md. Hasanul

Automatic Traffic Sign Recognition is paramount in modern transportation systems, motivating several research endeavors to focus on performance improvement by utilizing large-scale datasets. As the appearance of traffic signs varies across countries,

Externí odkaz: http://arxiv.org/abs/2409.14852

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Akademický článek

Effectiveness of a tubular heat exchanger and a novel perforated rectangular flow-deflector type baffle plate with opposing orientation

Autor: Rahman, Md Atiqur

Publikováno v: World Journal of Engineering, 2023, Vol. 21, Issue 6, pp. 1086-1094.

Externí odkaz: http://www.emeraldinsight.com/doi/10.1108/WJE-06-2023-0233

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Akademický článek

Revisiting the puzzle of capital structure determinants: an empirical study based on UK firms

Autor: Rahman, Md. Atiqur, Hossain, Tanjila, Sen, Kanon Kumar

Publikováno v: Arab Gulf Journal of Scientific Research, 2023, Vol. 42, Issue 4, pp. 1359-1378.

Externí odkaz: http://www.emeraldinsight.com/doi/10.1108/AGJSR-04-2023-0162

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Evaluating the Reliability of CNN Models on Classifying Traffic and Road Signs using LIME

Autor: Rahman, Md. Atiqur, Tanim, Ahmed Saad, Islam, Sanjid, Pranto, Fahim, Shahariar, G. M., Shawon, Md. Tanvir Rouf

The objective of this investigation is to evaluate and contrast the effectiveness of four state-of-the-art pre-trained models, ResNet-34, VGG-19, DenseNet-121, and Inception V3, in classifying traffic and road signs with the utilization of the GTSRB

Externí odkaz: http://arxiv.org/abs/2309.05747

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