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Showing 20 of 147 academic articles

Introduction Neural networks in remote sensing

Peter M. Atkinson, Adrian R. L. Tatnall • International Journal of Remote Sensing (1997)

Abstract. Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that ...

OPENALEX DOI: https://doi.org/10.1080/014311697218700

Credit card fraud detection in the era of disruptive technologies: A systematic review

Asma Cherif, Arwa Badhib, Heyfa Ammar, Suhair Alshehri et al. • Journal of King Saud University: Computer and Information Sciences (2023)

Credit card fraud is becoming a serious and growing problem as a result of the emergence of innovative technologies and communication methods, such as contactless payment. In this article, we present an in-depth review of cutting-edge resea...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jksuci.2022.11.008

Review: Deep Learning on 3D Point Clouds

Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing (2020)

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...

OPENALEX cc-by DOI: https://doi.org/10.3390/rs12111729

An Efficient Distributed Reinforcement Learning Architecture for Long-Haul Communication Between Actors and Learner

Shin Morishima, Hiroki Matsutani • IEEE Access (2024)

A computing cluster that interconnects multiple compute nodes is used to accelerate distributed reinforcement learning that uses DQN (Deep Q-Network). In distributed reinforcement learning, actor nodes acquire experiences by interacting wit...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3402835

Deep learning with COTS HPC systems

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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IntelliScheduler: an edge-cloud computing environment hybrid deep learning framework for task scheduling based on learning

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...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-41330-8

An Automated Image-Based Dietary Assessment System for Mediterranean Foods

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...

DOAJ Open Access (DOAJ) DOI: 10.1109/OJEMB.2023.3266135

Recurrent Neural Networks Based Online Behavioural Malware Detection Techniques for Cloud Infrastructure

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...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2021.3077498

Ship Detection With SAR C-Band Satellite Images: A Systematic Review

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 ...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2024.3437187

Deep Learning With Edge Computing: A Review

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...

OPENALEX DOI: https://doi.org/10.1109/jproc.2019.2921977

IoT-RiceMobileNet: An improved lightweight MobileNetV2 Model for real-time multi-class rice disease detection using IoT.

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...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0356383

Proactive caching in cloud and D2D assisted multi-tier cellular networks

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...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.4004

Decentralized Distributed Sequential Neural Networks Inference on Low-Power Microcontrollers in Wireless Sensor Networks: A Predictive Maintenance Case Study

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...

DOAJ Open Access (DOAJ) DOI: 10.3390/s25154595

Neural Networks for Machine Learning

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...

OPENALEX Open Access DOI: https://doi.org/10.1017/9781139051699.031

Leveraging Cloud Technology for Personalized Multiple Sclerosis Care: A Comprehensive Data Management and Visualization Approach

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...

DOAJ Open Access (DOAJ)

Machine Learning from Theory to Algorithms: An Overview

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...

OPENALEX cc-by DOI: https://doi.org/10.1088/1742-6596/1142/1/012012

A Novel Approach for Multichannel Epileptic Seizure Classification Based on Internet of Things Framework Using Critical Spectral Verge Feature Derived from Flower Pollination Algorithm

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...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22239302