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V Geetha, C.K. Gomathy, Mr.D.Sri Datta Vallab Yaratha Yagn, Sai Praneesh • INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
(2023)
Natural Language Processing (NLP) is a rapidly evolving field in the intersection of computer science, artificial intelligence, and linguistics. This article provides an overview of NLP, tracing its historical development from early rule-ba...
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Open Access
DOI: https://doi.org/10.55041/ijsrem27094
Stéphane M. Meystre, Peter John Haug • BMC Medical Informatics and Decision Making
(2005)
BACKGROUND: The medical problem list is an important part of the electronic medical record in development in our institution. To serve the functions it is designed for, the problem list has to be as accurate and timely as possible. However,...
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DOI: https://doi.org/10.1186/1472-6947-5-30
PMC: 1208893
Emily M. Bender, Batya Friedman • Transactions of the Association for Computational Linguistics
(2018)
In this paper, we propose data statements as a design solution and professional practice for natural language processing technologists, in both research and development. Through the adoption and widespread use of data statements, the field ...
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DOI: https://doi.org/10.1162/tacl_a_00041
Yang Liu, Meng Zhang • Computational Linguistics
(2017)
Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...
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cc-by-nc-nd
DOI: https://doi.org/10.1162/coli_r_00312
V Ranjit, Suchitra Naik • International Journal of Computing Algorithm
(2023)
A branch of computer science and AI called natural language processing is focused on how computers and human languages interact.In order for computers to interpret written and spoken human language without the use of computer-driven languag...
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DOI: https://doi.org/10.20894/ijcoa.101.012.002.001
Tatwadarshi P. Nagarhalli, Vinod Moreshwar Vaze, Nirav Pravinsinh Rana • International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV)
(2021)
The recent times have seen unprecedented growth in research and development in the field of Artificial Intelligence and its allied fields, subfields, like Machine Learning, Deep Learning and Natural Language Processing. The new found excite...
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DOI: https://doi.org/10.1109/icicv50876.2021.9388380
Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali, Jong‐Seok Lee et al. • Artificial Intelligence Review
(2023)
Abstract Over the last decade, neural networks have reached almost every field of science and become a crucial part of various real world applications. Due to the increasing spread, confidence in neural network predictions has become more a...
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DOI: https://doi.org/10.1007/s10462-023-10562-9
Abhijit S. Pandya, Robert B. Macy • CRC Press eBooks
(2021)
From the Publisher:
The addition of artificial neural network computing to traditionalpattern recognition has given rise to a new, different, and more powerful methodology that is presented in this interesting book. This is a practical gui...
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DOI: https://doi.org/10.1201/9780138744274
Igor I. Baskin, David Alan Winkler, Igor V. Tetko • Expert Opinion on Drug Discovery
(2016)
INTRODUCTION: Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to cho...
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DOI: https://doi.org/10.1080/17460441.2016.1201262
Nachimuthu Karunanithi, Darrell Whitley, Yashwant K. Malaiya • IEEE Software
(1992)
It is shown that neural network reliability growth models have a significant advantage over analytic models in that they require only failure history as input and not assumptions about either the development environment or external paramete...
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DOI: https://doi.org/10.1109/52.143107
Alison Carling • Sigma Press eBooks
(1992)
A background to the history of neural networks is provided in this book, in a way accessible to readers without a formal knowledge of computer science or advanced biology. It describes the major learning algorithms, the constraints of neuro...
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Gongbo Zhang • IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
(2000)
Classification is one of the most active research and application areas of neural networks. The literature is vast and growing. This paper summarizes some of the most important developments in neural network classification research. Specifi...
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DOI: https://doi.org/10.1109/5326.897072
Sebastian Kujawa, Gniewko Niedbała • Agriculture
(2021)
Artificial neural networks are one of the most important elements of machine learning and artificial intelligence. They are inspired by the human brain structure and function as if they are based on interconnected nodes in which simple proc...
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DOI: https://doi.org/10.3390/agriculture11060497
Steven Walczak • Advances in computer and electrical engineering book series
(2018)
This chapter examines the history of artificial neural networks research through the present day. The components of artificial neural network architectures and both unsupervised and supervised learning methods are discussed. Although a step...
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DOI: https://doi.org/10.4018/978-1-5225-7368-5.ch004
Qiming Zhang, Haoyi Yu, Martina Barbiero, Baokai Wang et al. • Light Science & Applications
(2019)
The growing demands of brain science and artificial intelligence create an urgent need for the development of artificial neural networks (ANNs) that can mimic the structural, functional and biological features of human neural networks. Nano...
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DOI: https://doi.org/10.1038/s41377-019-0151-0
PMC: 6504946
Byoung S. Kim, Anthony J. Calise • Journal of Guidance Control and Dynamics
(1997)
The theoretical developmentofa direct adaptivetracking controlarchitectureusingneuralnetworks ispresented. Emphasis is placed on utilization of neural networks in a ight control architecture based on feedback linearization of the aircraft...
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DOI: https://doi.org/10.2514/2.4029
Osama Moselhi, Tarek Hegazy, Paul Fazio • Journal of Construction Engineering and Management
(1991)
The competitive and risk‐averse nature of the construction industry and its heuristic problem‐solving needs, among other reasons, have contributed to the development of nontraditional decision‐making tools. Research in artificial intelligen...
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DOI: https://doi.org/10.1061/(asce)0733-9364(1991)117:4(606)
Dana H. Ballard • National Conference on Artificial Intelligence
(1987)
In the development of large-scale knowledge networks much recent progress has been inspired by connections to neurobiology. An important component of any neural network is an accompanying learning algorithm. Such an algorithm, to be biologi...
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(1995)
A general introduction to the subject of artificial neural networks is given and the tenuous relationship of neural networks to the biological neuron structure of the brain is also briefly outlined. The development of artificial neural netw...
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DOI: https://doi.org/10.1109/etd.1995.403491
Robert E. Uhrig • Annual Conference of the IEEE Industrial Electronics Society (IECON)
(2002)
A neural network is a data processing system consisting of a large number of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks ...
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DOI: https://doi.org/10.1109/iecon.1995.483329