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Academic Articles & Research Papers
Showing 20 of 748 academic articles
Binayak Panda, Sudhanshu Shekhar Bisoyi, Sidhanta Panigrahy • PeerJ Computer Science
(2023)
Dependence on the internet and computer programs demonstrates the significance of computer programs in our day-to-day lives. Such demands motivate malware developers to create more malware, both in terms of quantity and variety. Researchers...
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Open Access (DOAJ)
DOI: 10.7717/peerj-cs.1677
Laura ONAC • Studia Universitatis Babes-Bolyai: Series Informatica
(2019)
Plant recognition represents a challenging computer vision problem due to the great variations of shape and texture among plant organs, within the same species. This paper proposes a light-weight, but reasonably deep Convolutional Neural Ne...
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Open Access (DOAJ)
DOI: 10.24193/subbi.2019.1.01
Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar et al. • IEEE Access
(2025)
This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regim...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3567410
Theodore Warsavage, Fuyong Xing, Anna E Barón, William J Feser et al. • PLoS ONE
(2020)
We present a case study for implementing a machine learning algorithm with an incremental value framework in the domain of lung cancer research. Machine learning methods have often been shown to be competitive with prediction models in some...
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Open Access (DOAJ)
DOI: 10.1371/journal.pone.0231468
Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials
(2026)
The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...
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Open Access (DOAJ)
DOI: 10.3390/nano16030179
Fahad Ahmed Khokhar, Tommaso Zoppi, Luigi Cennini, Andrea Ceccarelli et al. • Scientific Reports
(2026)
Abstract The last decade has seen a surging opportunity for developing autonomous systems (e.g., fully autonomous driving, computer-guided robotic surgery, mobile robots for inspections and surveillance, and manufacturing robots) to relieve...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-45091-2
Azim Keshavarzian Nodehi, Nasrollah Moghadam Charkari • Machine Learning with Applications
(2022)
Word Sense Disambiguation (WSD) is one of the earliest problems in natural language processing which aims to determine the correct sense of words in context. The semantic information provided by WSD systems is highly beneficial to many task...
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Open Access (DOAJ)
DOI: 10.1016/j.mlwa.2022.100369
Dhurgham Ali Mohammed, Kalyani A. Patel • ICTACT Journal on Soft Computing
(2025)
In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...
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Open Access (DOAJ)
DOI: 10.21917/ijsc.2025.0518
Matthias S. Treder • Frontiers in Neuroscience
(2020)
MVPA-Light is a MATLAB toolbox for multivariate pattern analysis (MVPA). It provides native implementations of a range of classifiers and regression models, using modern optimization algorithms. High-level functions allow for the multivaria...
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Open Access (DOAJ)
DOI: 10.3389/fnins.2020.00289
Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe et al. • Nature Communications
(2022)
Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...
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DOI: https://doi.org/10.1038/s41467-022-27980-y
PMC: 8828720
Willian Borges De Lemos, Lucas De Angelo Martins Ribeiro, Vanessa Telles Da Silva, Alessandro De Lima Bicho et al. • IEEE Access
(2025)
Graph embeddings map graph-structured data into vector spaces for machine learning tasks. In Graph Neural Networks (GNNs), these embeddings are computed through message passing and support tasks such as node classification, link prediction ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3643796
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
Aleksanteri Hamalainen, Aku Karhinen, Jesse Miettinen, Zacharias Dahl et al. • IEEE Access
(2025)
Rotating machines are extremely common in many industries, and their maintenance involves substantial costs and labor. Most recent studies aiming to automate fault diagnosis have focused on deep learning, but industry adoption has been slow...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3627885
Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing
(2026)
Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...
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Open Access (DOAJ)
DOI: 10.3390/rs18172862
Rafael A. Irizarry • Chapman & Hall/CRC eBooks
(2019)
The machine learning approach is to train an algorithm using a dataset for which the people do know the outcome, and then apply this algorithm in the future to make a prediction when they don't know the outcome. In this chapter, the authors...
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DOI: https://doi.org/10.1201/9780429341830-27
Edoardo Bizzotto, Guido Zampieri, Laura Treu, Pasquale Filannino et al. • Computational and Structural Biotechnology Journal
(2024)
Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on...
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Open Access (DOAJ)
DOI: 10.1016/j.csbj.2024.05.040
Binbin Chen, Shengjie Long • IEEE Access
(2020)
In traditional financial analysis discriminant analyses with statistic methods are considered as primary and widely applied corporate credit rating bases in which human impact plays an essential role. Machine learning approaches enormously ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3036469
Bardia Abbasi, Daniel M. Goldenholz • Epilepsia
(2019)
Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recogn...
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Open Access
DOI: https://doi.org/10.1111/epi.16333
PMC: 9897263
Zhao D, Qin D, Yin L, Yang Q • Pharmacogenomics and Personalized Medicine
(2023)
Danya Zhao,1 Danping Qin,2 Liming Yin,3 Qiang Yang4 1The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 2Department of Gastroenterology, The First Affiliated Hospital of Zheji...
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Open Access (DOAJ)
Alexandre Abraham, Fabián Pedregosa, Michael Eickenberg, Philippe Gervais et al. • Frontiers in Neuroinformatics
(2014)
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series....
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DOI: https://doi.org/10.3389/fninf.2014.00014
PMC: 3930868