Výsledky vyhledávání - "deep learning: applications"

Akademický článek

Football trajectory prediction and real-time feedback mechanism based on Temporal Convolutional Network

Autor: Chen Zhang, Xinyao Xi, Xinming Wang, Zhihao Zhang

Publikováno v: Alexandria Engineering Journal, Vol 114, Iss , Pp 476-484 (2025)

In modern football matches, athlete trajectory analysis and real-time feedback play a crucial role in tactical planning and game management. Traditional trajectory prediction methods struggle to provide accurate real-time feedback due to an insuffici

Externí odkaz: https://doaj.org/article/9441dce8796644bea943fd622f9a3a00

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Akademický článek

Humidification potential optimization of various membranes for proton exchange membrane fuel cell: Experiments and deep learning assisted metaheuristics

Autor: Imtiyaz Hussain, Uzair Sajjad, Naseem Abbas, Muhammad Sultan, Thangavel Sangeetha, Hafiz Muhammad Ali, Zafar Said, Wei-Mon Yan

Publikováno v: Alexandria Engineering Journal, Vol 87, Iss , Pp 424-447 (2024)

This study addresses the durability and performance challenges in Proton Exchange Membrane Fuel Cell (PEMFC) technology, primarily focusing on optimal humidity management. Acknowledging that, beyond technical aspects, the broader commercialization of

Externí odkaz: https://doaj.org/article/013a4f5968464b979076f6c085131946

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Akademický článek

A Novel Technique to Support Deep Learning Applications in a Model-Based Embedded Software Design Methodology

Autor: Jangryul Kim, Jaewoo Son, Soonhoi Ha

Publikováno v: IEEE Access, Vol 11, Pp 54869-54880 (2023)

As deep learning applications are getting popular in embedded systems, how to support deep learning applications in the model-based embedded software design methodology becomes a challenging problem. A previous solution is to represent each deep lear

Externí odkaz: https://doaj.org/article/60b3eb2af71549589f13b879617b3e1d

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Akademický článek

Analysis of Deep Learning Development Platforms and Their Applications in Sustainable Development within the Education Sector

Autor: Ouahi Mariame, Khoulji Samira, Laarbi Kerkeb Mohammed

Publikováno v: E3S Web of Conferences, Vol 477, p 00098 (2024)

Educational institutions use information and communication technologies effectively to meet the innovation requirements that will increase their competitiveness. In this context, the rapid progression of deep learning has become a focal point for edu

Externí odkaz: https://doaj.org/article/df1af49cc6f04a1ca689b94986d523a4

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Akademický článek

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Akademický článek

Quadruplet loss and SqueezeNets for Covid-19 detection from Chest-X rays

Autor: Pranshav Gajjar, Naishadh Mehta, Pooja Shah

Publikováno v: Computer Science Journal of Moldova, Vol 30, Iss 2(89), Pp 214-222 (2022)

The Coronavirus Pandemic triggered by SARS-CoV-2 has wreaked havoc on the planet and is expanding exponentially. While scanning methods, including CT scans and chest X-rays, are commonly used, artificial intelligence implementations are also deployed

Externí odkaz: https://doaj.org/article/c475033cfd4744a7887a25397e19b44d

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Akademický článek

A review of deep learning applications in human genomics using next-generation sequencing data

Autor: Wardah S. Alharbi, Mamoon Rashid

Publikováno v: Human Genomics, Vol 16, Iss 1, Pp 1-20 (2022)

Abstract Genomics is advancing towards data-driven science. Through the advent of high-throughput data generating technologies in human genomics, we are overwhelmed with the heap of genomic data. To extract knowledge and pattern out of this genomic d

Externí odkaz: https://doaj.org/article/a02989d1d801439ea249616ab04da1e9

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