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Academic Articles & Research Papers
Showing 20 of 142 academic articles
Adam Coates, Brody Huval, Tao Wang, David J. Wu et al. (2013)
Scaling up deep learning algorithms has been shown to lead to increased performance in benchmark tasks and to enable discovery of complex high-level features. Recent efforts to train extremely large networks (with over 1 billion parameters)...
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L. Raghavendar Raju, M. Venkata Krishna Reddy, Sridhar Reddy Surukanti, Gudlanarva Sudhakar et al. • Scientific Reports
(2026)
Abstract Edge–cloud computing has emerged as an important paradigm for modern Internet of Things (IoT) workflow applications, enabling low latency and on-demand resource allocation. In scenarios with heterogeneous deadlines and varying work...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-41330-8
Fotios S. Konstantakopoulos, Eleni I. Georga, Dimitrios I. Fotiadis • IEEE Open Journal of Engineering in Medicine and Biology
(2023)
Goal: The modern way of living has significantly influenced the daily diet. The ever-increasing number of people with obesity, diabetes and cardiovascular diseases stresses the need to find tools that could help in the daily intake of the n...
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Open Access (DOAJ)
DOI: 10.1109/OJEMB.2023.3266135
Jeffrey C. Kimmel, Andrew D. Mcdole, Mahmoud Abdelsalam, Maanak Gupta et al. • IEEE Access
(2021)
Several organizations are utilizing cloud technologies and resources to run a range of applications. These services help businesses save on hardware management, scalability and maintainability concerns of underlying infrastructure. Key clou...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3077498
Cyprien Alexandre, Rodolphe Devillers, David Mouillot, Raphael Seguin et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2024)
Detecting and tracking ships remotely is now required in a wide range of contexts, from military security to illegal immigration control, as well as the management of fisheries and marine protected areas. Among the available methods, radar ...
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Open Access (DOAJ)
DOI: 10.1109/JSTARS.2024.3437187
Jiasi Chen, Xukan Ran • Proceedings of the IEEE
(2019)
Deep learning is currently widely used in a variety of applications, including computer vision and natural language processing. End devices, such as smartphones and Internet-of-Things sensors, are generating data that need to be analyzed in...
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DOI: https://doi.org/10.1109/jproc.2019.2921977
Khawja Imran Masud, Md Yasin Zihad, Mehedi Hasan Shuvo, Mst Raonik Jannat et al. • PLoS ONE
(2026)
Early and real-time detection of rice leaf diseases (RLD) poses a significant challenge for farmers, especially in rural regions with limited access to advanced technology. Conventional deep learning models often require substantial computa...
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Open Access (DOAJ)
DOI: 10.1371/journal.pone.0356383
Elisabetta Doria • Agathón
(2022)
The research proposal reports the outcomes of a research track concerning the automation of the architectural census of technological elements in urban environments, aiming at the development of a monitoring and management system for the bu...
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Open Access (DOAJ)
DOI: 10.19229/2464-9309/12162022
Pengfei Li, Yue Jia • Sensors
(2026)
Diameter at breast height (DBH) is a fundamental structural parameter for forest inventory and ecological analysis. However, field-based measurements (e.g., diameter tape surveys) are labor-intensive and inefficient for large-scale applicat...
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Open Access (DOAJ)
DOI: 10.3390/s26092873
Ayaz Ahmad, Fawad Ahmad, Muhammad Suleman Khan, Adel Aldalbahi • PeerJ Computer Science
(2026)
Proactive caching in multi-tier cellular networks (MTCNs) is an efficient technique for alleviating heavy data traffic on backhaul links, thereby reducing content latency and increasing the overall cache hit ratio (CHR) and user satisfactio...
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Open Access (DOAJ)
DOI: 10.7717/peerj-cs.4004
Yernazar Bolat, Iain Murray, Yifei Ren, Nasim Ferdosian • Sensors
(2025)
The growing adoption of IoT applications has led to increased use of low-power microcontroller units (MCUs) for energy-efficient, local data processing. However, deploying deep neural networks (DNNs) on these constrained devices is challeng...
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Open Access (DOAJ)
DOI: 10.3390/s25154595
Richard F. Lyon • Cambridge University Press eBooks
(2017)
In order for a digital neocortex to learn a new skill, it will still require many iterations of education, just as a biological neocortex does, but once a single neocortex somewhere and at some time learns something, it can share that knowl...
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Open Access
DOI: https://doi.org/10.1017/9781139051699.031
Jose Manuel PINILLOS RUBIO, Minerva VIGUERA MORENO • Applied Medical Informatics
(2024)
This project develops a cloud-based solution for securely managing clinical data and patient-reported outcomes (PROMs) for multiple sclerosis (MS) patients. Utilizing REDCap for data collection, we incorporated clinical outcomes and PROMs f...
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Open Access (DOAJ)
Jafar Ahmad Abed Alzubi, Anand Nayyar, Akshi Kumar • Journal of Physics Conference Series
(2018)
The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which i...
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DOI: https://doi.org/10.1088/1742-6596/1142/1/012012
Dhanalekshmi Prasad Yedurkar, Shilpa P. Metkar, Fadi Al-Turjman, Thompson Stephan et al. • Sensors
(2022)
A novel approach for multichannel epilepsy seizure classification which will help to automatically locate seizure activity present in the focal brain region was proposed. This paper suggested an Internet of Things (IoT) framework based on a...
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Open Access (DOAJ)
DOI: 10.3390/s22239302
Sebastian Lins, Konstantin D. Pandl, Heiner Teigeler, Scott Thiebes et al. • Business & Information Systems Engineering
(2021)
Artificial intelligence Á Cloud computing Á Machine learning as a service 1 The Roots of Artificial Intelligence as a Service 1.1 The Emergence of Artificial Intelligence Services Artificial Intelligence (AI) is undoubtedly one of the most ...
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DOI: https://doi.org/10.1007/s12599-021-00708-w
Ł. Wilk, Ł. Wilk, D. Mielczarek, W. Ostrowski et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2022)
The use of deep machine learning methods for semantic classification of city mesh models is one of the current trends in geoscience development. Thanks to the thriving development of Convolutional Neural Networks (CNNs) it is now achievable...
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Open Access (DOAJ)
DOI: 10.5194/isprs-archives-XLIII-B2-2022-485-2022
Ke Guan, Markus Rupp, Thomas Kurner, Cesar Briso et al. • IEEE Access
(2020)
Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050, more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3037635
Alejandro Espinosa, Xavier Samos, Daniel Ulied, Jordi Marias et al. • International Journal of Computational Intelligence Systems
(2025)
Abstract As the usage of the edge-cloud continuum increases, Kubernetes presents itself as a solution that allows easy control and deployment of applications in these highly-distributed and heterogeneous environments. In this context, Artif...
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Open Access (DOAJ)
DOI: 10.1007/s44196-025-01073-2
Abhiraam Eranti, Yogesh Tewari, Rafael Palacios, Amar Gupta • IEEE Access
(2026)
Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2026.3672109