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Academic Articles & Research Papers
Showing 20 of 1,679 academic articles
Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu • Journal of Computational Chemistry
(2017)
The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning,...
OPENALEX
Open Access
DOI: https://doi.org/10.1002/jcc.24764
Shiv Singh, Neelu Jyothi Ahuja • Discover Computing
(2026)
Abstract The application of deep learning models in resource-constrained environments requires a trade-off among accuracy, efficiency, and interpretability a trilemma frequently neglected in conventional knowledge distillation (KD) approach...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s10791-026-10123-y
Sandipan Sikdar, Rachneet Sachdeva, Johannes Wachs, Johannes Wachs et al. • Frontiers in Big Data
(2022)
This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fdata.2021.771404
Wenqiang Liu, Li Yan, Ningning Ma, Gaozhou Wang et al. • Applied Sciences
(2024)
With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eli...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app14020774
Shaorong Zhang, Shaorong Zhang, Qihui Wang, Benxin Zhang et al. • Frontiers in Neuroscience
(2023)
IntroductionThe time, frequency, and space information of electroencephalogram (EEG) signals is crucial for motor imagery decoding. However, these temporal-frequency-spatial features are high-dimensional small-sample data, which poses signi...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnins.2023.1292724
Natasha Dropka, Stefan Ecklebe, Martin Holena • Crystals
(2021)
The aim of this study was to assess the aptitude of the recurrent Long Short-Term Memory (LSTM) neural networks for fast and accurate predictions of process dynamics in vertical-gradient-freeze growth of gallium arsenide crystals (VGF-GaAs)...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/cryst11020138
Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn • BMC Medical Imaging
(2025)
Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several ...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12880-025-01643-y
Seonwoo Min, Byunghan Lee, Sungroh Yoon • Briefings in Bioinformatics
(2016)
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-th...
OPENALEX
Open Access
DOI: https://doi.org/10.1093/bib/bbw068
Esraa Khatab, Ahmed Onsy, Ahmed Abouelfarag • Sensors
(2022)
One of the primary tasks undertaken by autonomous vehicles (AVs) is object detection, which comes ahead of object tracking, trajectory estimation, and collision avoidance. Vulnerable road objects (e.g., pedestrians, cyclists, etc.) pose a g...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s22041663
Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering
(2022)
Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrmge.2022.01.012
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
Xin Qian, Yu Li, Xianghui Zhang, Heng Guo et al. • Frontiers in Cardiovascular Medicine
(2022)
BackgroundCardiovascular diseases (CVD) are currently the leading cause of premature death worldwide. Model-based early detection of high-risk populations for CVD is the key to CVD prevention. Thus, this research aimed to use machine learni...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fcvm.2022.854287
Younggill Son, Woongchul Choi • Batteries
(2024)
With the global surge in electric vehicle (EV) deployment, driven by enhanced environmental regulations and efforts to reduce transportation-related greenhouse gas emissions, managing the life cycle of Li-ion batteries becomes more critical...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/batteries10060191
Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences
(2024)
Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrras.2024.101172
Sun Ping • Materials Research Express
(2026)
Polymer solar cells (PSCs) rely on labor-intensive trial-and-error experiments to optimize power conversion efficiency (PCE), due to complex coupling of molecular electronic properties, blend morphology and fabrication parameters. This work...
DOAJ
Open Access (DOAJ)
DOI: 10.1088/2053-1591/aeaacc
Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data
(2026)
Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40537-026-01475-9
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...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s26092873
Binghui Wang, Neil Zhenqiang Gong • IEEE Symposium on Security and Privacy (S&P)
(2018)
Hyperparameters are critical in machine learning, as different hyperparameters often result in models with significantly different performance. Hyperparameters may be deemed confidential because of their commercial value and the confidentia...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/sp.2018.00038
Sergio Muñoz, Carlos Á. Iglesias • Big Data and Cognitive Computing
(2024)
The proliferation of fake news threatens the integrity of information ecosystems, creating a pressing need for effective and interpretable detection mechanisms. Recent advances in machine learning, particularly with transformer-based models...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bdcc8100129
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