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Academic Articles & Research Papers
Showing 20 of 94 academic articles
Kai Wang, Kunjian Wen, Yanping Chen, Yongbin Qin • Scientific Reports
(2025)
Abstract Mapping a sentence into a two-dimensional (2D) representation can flatten nested semantic structures and build multi-granular span dependencies in named entity recognition. Existing approaches to recognizing named entities often cl...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-025-87722-0
Muhammad Faseeh, Misbah Bibi, Murad Ali Khan, Atif Rizwan et al. • IEEE Access
(2024)
Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3485089
Neofytos Dimitriou, Ognjen Arandjelović • Information
(2022)
Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normaliz...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info13070337
Nazeer Bilal, Pradeep Carol Santhosh, Vargas Patricia A., Erden Mustafa Suphi et al. • Manufacturing Review
(2025)
This study presents a comprehensive study of a novel Contact-Based Pose Estimation Method (CBPEM) for enhancing precision in robotic assembly processes within digital twin frameworks. Conventional pose detection methods, such as laser and c...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/mfreview/2025004
Klemen Istenič, Nuno Gracias, Aurélien Arnaubec, Javier Escartín et al. • Remote Sensing
(2019)
Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This pa...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs11182093
Yong Xu, Chaoda Zheng, Ruotao Xu, Yuhui Quan • IEEE Access
(2019)
Recognition of 3D shapes is a fundamental task in computer vision. In recent years, view-based deep learning has emerged as an effective approach for 3D shape recognition. Most existing view-based methods treat the views of an object as an ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2934650
Aleksey Viktorovich Skorokhodov, Sergey Vladimirovich Aksenov, Andrey Vladimirovich Aksenov, Dmitriy Nikolaevich Laykom • Известия Томского политехнического университета: Инжиниринг георесурсов
(2017)
The relevance of the research is caused by the necessity to develop algorithms and software to classify the cloud types based on single-layer cloud on the satellite images received from MODIS spectral radiometer used in Terra and Aqua remot...
DOAJ
Open Access (DOAJ)
Timothée Corchia, Bertrand Bonan, Nemesio Rodríguez-Fernández, Gabriel Colas et al. • Remote Sensing
(2023)
In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (ISBA) land surface model using Meteo-France’s global Land Data Assimilation System (LDAS-M...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs15174258
Rui Zhang, Ranran Zhou, Zuting Zhong, Haifeng Qi et al. • Sensors
(2024)
Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate. However, multi-class classification of ECG signals based on bCN...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s24227207
Ye Yuan, Yongtong Zhu, Jiaqi Wang, Ruoshi Li et al. • Frontiers in Neuroscience
(2023)
IntroductionSpiking neural networks (SNNs), inspired by biological neural networks, have received a surge of interest due to its temporal encoding. Biological neural networks are driven by multiple plasticities, including spike timing-depen...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnins.2023.1224752
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness et al. • Proceedings of the National Academy of Sciences
(2017)
The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitabl...
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Open Access
DOI: https://doi.org/10.1073/pnas.1611835114
PMC: 5380101
Zhiquan He, Meshari Alazmi, Jingfen Zhang, Dong Xu • PLoS ONE
(2013)
Quality assessment (QA) for predicted protein structural models is an important and challenging research problem in protein structure prediction. Consensus Global Distance Test (CGDT) methods assess each decoy (predicted structural model) b...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0074006
Christoph Bergmeir, José M. Benítez • Journal of Statistical Software
(2012)
Neural networks are important standard machine learning procedures for classification and regression. We describe the R package RSNNS that provides a convenient interface to the popular Stuttgart Neural Network Simulator SNNS. The main feat...
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DOI: https://doi.org/10.18637/jss.v046.i07
Sarnovský M., Nina A., Popović L.Č., Srećković V. et al. • Serbian Astronomical Journal
(2026)
Gamma-ray bursts (GRBs) are recognized as the most energetic and luminous astrophysical phenomena whose high-energy photons can ionize atmospheric
particles and thus affect electrical conductivity. Consequently,
electromagnetic waves ...
DOAJ
Open Access (DOAJ)
DOI: 10.2298/SAJ2612107S
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai et al. • npj Digital Medicine
(2018)
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...
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DOI: https://doi.org/10.1038/s41746-018-0029-1
PMC: 6550175
JongCheol Pyo, Hongtao Duan, Mayzonee Ligaray, Minjeong Kim et al. • Remote Sensing
(2020)
Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estim...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs12071073
Sara Sheehan, Yun S. Song • PLoS Computational Biology
(2016)
Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep...
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DOI: https://doi.org/10.1371/journal.pcbi.1004845
PMC: 4809617
Nitin Kumar Chauhan, Krishna Pal Singh • International Conference on Computing, Power and Communication Technologies (GUCON)
(2018)
In now days, deep learning has become a prominent and emerging research area in computer vision applications. Deep learning permits the multiple layers models for computation to learn representations of data by processing in their original ...
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DOI: https://doi.org/10.1109/gucon.2018.8675097
ZHANG Bin1, YIN Haoyu2, ZHANG Tengfei2, WANG Jiangyu1, LU Di1, WANG Lianjie1 • Yuanzineng kexue jishu
(2026)
To meet the computational efficiency requirements for multi-physics simulations in the design and development of advanced reactor cores, a neural network-based acceleration method was investigated for multi-physics coupling calculations in ...
DOAJ
Open Access (DOAJ)
DOI: 10.7538/yzk.2025.youxian.0668
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 ...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3426723