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Academic Articles & Research Papers
Showing 20 of 689 academic articles
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Swarnendu Ghosh, Nibaran Das, Ishita Das, Ujjwal Maulik • ACM Computing Surveys
(2019)
The machine learning community has been overwhelmed by a plethora of deep learning--based approaches. Many challenging computer vision tasks, such as detection, localization, recognition, and segmentation of objects in an unconstrained envi...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3329784
Hui Fang, Danning Zhang, Yiheng Shu, Guibing Guo • ACM Transactions on Information Systems
(2020)
In the field of sequential recommendation, deep learning--(DL) based methods have received a lot of attention in the past few years and surpassed traditional models such as Markov chain-based and factorization-based ones. However, there is ...
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Open Access
DOI: https://doi.org/10.1145/3426723
Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing
(2022)
Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs14174235
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
Noritaka Fukunaga, Sho Sanami, Hiroya Kitasaka, Yuji Tsuzuki et al. • Reproductive Medicine and Biology
(2020)
Abstract Purpose To establish an automated pronuclei determination system by analysis using deep learning technology which is able to effectively learn with limited amount of supervised data. Methods An algorithm was developed by explicitly...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/rmb2.12331
Dinggang G. Shen, Guorong Wu A, Heung‐Il Suk • Annual Review of Biomedical Engineering
(2017)
This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical image...
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Open Access
DOI: https://doi.org/10.1146/annurev-bioeng-071516-044442
PMC: 5479722
Justin M. Johnson, Taghi M. Khoshgoftaar • Journal Of Big Data
(2019)
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in...
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DOI: https://doi.org/10.1186/s40537-019-0192-5
Gabriel de Sousa Meira, João Victor Ferreira Guedes, Edilson de Souza Bias • Drones
(2024)
The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/drones8070341
Dimitrios Papamartzivanos, Felix Gomez Marmol, Georgios Kambourakis • IEEE Access
(2019)
The intrusion detection systems (IDSs) are essential elements when it comes to the protection of an ICT infrastructure. A misuse IDS is a stable method that can achieve high attack detection rates (ADR) while keeping false alarm rates under...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2893871
Ognjen Radišić-Aberger, Peter Burggräf, Fabian Steinberg, Alexander Becher et al. • Supply Chain Analytics
(2024)
By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.sca.2024.100087
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
Irfan Kareem, Syed Farooq Ali, Muhammad Bilal, Muhammad Shehzad Hanif • PLoS ONE
(2024)
Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in th...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0314959
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
Hafsa Habehh, Suril Gohel • Current Genomics
(2021)
Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, among...
OPENALEX
Open Access
DOI: https://doi.org/10.2174/1389202922666210705124359
PMC: 8822225
Dana Pessach, Erez Shmueli • ACM Computing Surveys
(2022)
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college ad...
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DOI: https://doi.org/10.1145/3494672
Sumesh Kharnotia, Bhavna Arora, Ravdeep Kour • ICT Express
(2026)
The extensive embrace of Android has amplified malware risks, resulting in a need for better detection methods. This article investigates the area of static analysis, which analyses applications without execution by examining code and manif...
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Open Access (DOAJ)
DOI: 10.1016/j.icte.2026.01.005
Sun-Feel Yang, So-Won Choi, Eul-Bum Lee • Energies
(2023)
The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affe...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/en16114271
Francesco Carnazza, Federico Carollo, Dominik Zietlow, Sabine Andergassen et al. • New Journal of Physics
(2022)
Full information about a many-body quantum system is usually out-of-reach due to the exponential growth—with the size of the system—of the number of parameters needed to encode its state. Nonetheless, in order to understand the complex phen...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/1367-2630/ac7df6
Johannes Leiner, Vincent Pellissier, Sebastian König, Sven Hohenstein et al. • Respiratory Research
(2022)
Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both i...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12931-022-02180-w