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Academic Articles & Research Papers
Showing 20 of 648 academic articles
James A. Anderson • The MIT Press eBooks
(1995)
An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain funct...
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DOI: https://doi.org/10.7551/mitpress/3905.001.0001
Enrique González-Plaza, David García, Jesús-Ignacio Prieto • Inventions
(2023)
Stirling engines are currently of interest due to their adaptability to a wide range of energy sources. Since simple tools are needed to guide the sizing of prototypes in preliminary studies, this paper proposes two groups of simple models ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/inventions8040088
Jin Liu, Yi Feng Pan, Min Li, Ziyue Chen et al. • Big Data Mining and Analytics
(2018)
Deep learning provides exciting solutions in many fields, such as image analysis, natural language processing, and expert system, and is seen as a key method for various future applications. On account of its non-invasive and good soft tiss...
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DOI: https://doi.org/10.26599/bdma.2018.9020001
Z. Karami • Fanāvarī-i āmūzish
(2023)
Background and Objectives: In order to solve the problem of education in complex and unstructured domains, Spiro and his colleagues proposed the theory of cognitive flexibility, in which they advocated multiple forms of pedagogical models, ...
DOAJ
Open Access (DOAJ)
DOI: 10.22061/tej.2023.9686.2885
Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan et al. • BMC Psychiatry
(2025)
Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12888-025-07196-2
Heang‐Ping Chan, Lubomir M. Hadjiiski, Ravi K. Samala • Medical Physics
(2020)
Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then ...
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Open Access
DOI: https://doi.org/10.1002/mp.13764
PMC: 7293164
Yijia WAN, Liping GU • Nongye tushu qingbao xuebao
(2024)
[Purpose/Significance] To explore in depth the acceptance and usage habits of AIGC tools by graduate students in the process of academic research, and to promote the positive attention and application of emerging technologies by graduate st...
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Open Access (DOAJ)
DOI: 10.13998/j.cnki.issn1002-1248.24-0716
D. Guest, Kyle Stuart Cranmer, Daniel Whiteson • Annual Review of Nuclear and Particle Science
(2018)
Machine learning has played an important role in the analysis of high-energy physics data for decades. The emergence of deep learning in 2012 allowed for machine learning tools which could adeptly handle higher-dimensional and more complex ...
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Open Access
DOI: https://doi.org/10.1146/annurev-nucl-101917-021019
Yanming Yang, Xin Xia, David Lo, John Grundy • ACM Computing Surveys
(2021)
In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstr...
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Open Access
DOI: https://doi.org/10.1145/3505243
Toke T. Høye, Johanna Ärje, Kim Bjerge, Oskar Liset Pryds Hansen et al. • Proceedings of the National Academy of Sciences
(2021)
ABSTRACT Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phe...
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DOI: https://doi.org/10.1073/pnas.2002545117
PMC: 7812775
Yair Rivenson, Zoltán S. Göröcs, Harun Günaydın, Yibo Zhang et al. • Optica
(2017)
We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired ...
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Open Access
DOI: https://doi.org/10.1364/optica.4.001437
Mufti Mahmud, M. Shamim Kaiser, T. Martin McGinnity, Amir Hussain • Cognitive Computation
(2021)
Recent technological advancements in data acquisition tools allowed life scientists to acquire multimodal data from different biological application domains. Categorized in three broad types (i.e. images, signals, and sequences), these data...
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DOI: https://doi.org/10.1007/s12559-020-09773-x
PMC: 7783296
Khoa Anh Tran, Olga Kondrashova, Andrew Peter Bradley, Elizabeth D. Williams et al. • Genome Medicine
(2021)
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning acr...
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DOI: https://doi.org/10.1186/s13073-021-00968-x
PMC: 8477474
Luke de Oliveira • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
(2022)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07%282016%29069
Luke de Oliveira, Michael Kagan, Lester W. Mackey, Benjamin Philip Nachman et al. • Journal of High Energy Physics
(2016)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07(2016)069
Alexander Craik, Yongtian He, Jose Luis Contreras-Vidal • Journal of Neural Engineering
(2019)
OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...
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DOI: https://doi.org/10.1088/1741-2552/ab0ab5
Siripen Pongpaichet, Boonyapat Sukosit, Chitchaya Duangtanawat, Jiramed Jamjongdamrongkit et al. • IEEE Access
(2024)
Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, espec...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3363879
Jing Li, Aixin Sun, Jianglei Han, Chenliang Li • IEEE Transactions on Knowledge and Data Engineering
(2020)
Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NER always serves as the foundation for many natural language ...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981314
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
Chaoyun Zhang, Paul Patras, Hamed Haddadi • IEEE Communications Surveys & Tutorials
(2019)
The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traff...
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Open Access
DOI: https://doi.org/10.1109/comst.2019.2904897