Výsledky vyhledávání - "Munir, Arslan"

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Empirical Measurements of AI Training Power Demand on a GPU-Accelerated Node

Autor: Latif, Imran, Newkirk, Alex C., Carbone, Matthew R., Munir, Arslan, Lin, Yuewei, Koomey, Jonathan, Yu, Xi, Dong, Zhiuha

The expansion of artificial intelligence (AI) applications has driven substantial investment in computational infrastructure, especially by cloud computing providers. Quantifying the energy footprint of this infrastructure requires models parameteriz

Externí odkaz: http://arxiv.org/abs/2412.08602

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Kniha

Accelerators for Convolutional Neural Networks. [elektronicky zdroj]

Autor: Munir, Arslan

Externí odkaz: Kolekce e-knih KNAV (Registrovani uzivatele: plny text online 5 minut, dalsi pristup na vyzadani. Registered users: full text online 5 minutes, further access on request.)

Kniha

Modeling and optimization of parallel and distributed embedded systems / Arslan Munir, Ann Gordon-Ross, Sanjay Ranka. [elektronicky zdroj]

Autor: Munir, Arslan, author

Externí odkaz: Kolekce e-knih KNAV

Akademický článek

Some new fractional corrected Euler-Maclaurin type inequalities for function whose second derivatives are s-convex function.

Autor: Munir, Arslan¹ (AUTHOR), Vivas-Cortez, Miguel² (AUTHOR) mjvivas@puce.edu.ec, Qayyum, Ather^3,4 (AUTHOR), Budak, Hüseyin⁵ (AUTHOR), Faiz, Irza⁶ (AUTHOR), Supadi, Siti Suzlin³ (AUTHOR)

Publikováno v: Mathematical & Computer Modelling of Dynamical Systems. Dec2024, Vol. 30 Issue 1, p543-566. 24p.

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ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos

Autor: Wensel, James, Ullah, Hayat, Munir, Arslan

Human activity recognition is an emerging and important area in computer vision which seeks to determine the activity an individual or group of individuals are performing. The applications of this field ranges from generating highlight videos in spor

Externí odkaz: http://arxiv.org/abs/2208.07929

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Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Framework

Autor: Ullah, Hayat, Munir, Arslan

Vision-based human activity recognition has emerged as one of the essential research areas in video analytics domain. Over the last decade, numerous advanced deep learning algorithms have been introduced to recognize complex human actions from video

Externí odkaz: http://arxiv.org/abs/2208.05034

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Akademický článek

H-QNN: A Hybrid Quantum–Classical Neural Network for Improved Binary Image Classification.

Autor: Hafeez, Muhammad Asfand¹ (AUTHOR) mhafeez2024@fau.edu, Munir, Arslan¹ (AUTHOR) arslanm@fau.edu, Ullah, Hayat¹ (AUTHOR)

Publikováno v: AI. Sep2024, Vol. 5 Issue 3, p1462-1481. 20p.

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Phantom: A High-Performance Computational Core for Sparse Convolutional Neural Networks

Autor: Qureshi, Mahmood Azhar, Munir, Arslan

Sparse convolutional neural networks (CNNs) have gained significant traction over the past few years as sparse CNNs can drastically decrease the model size and computations, if exploited befittingly, as compared to their dense counterparts. Sparse CN

Externí odkaz: http://arxiv.org/abs/2111.05002

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