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Academic Articles & Research Papers
Showing 20 of 2,365 academic articles
Sonit Singh • arXiv (Cornell University)
(2018)
With rise of digital age, there is an explosion of information in the form of news, articles, social media, and so on. Much of this data lies in unstructured form and manually managing and effectively making use of it is tedious, boring and...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1807.02383
Imane Guellil, Houda Saâdane, Faiçal Azouaou, Billel Gueni et al. • Journal of King Saud University - Computer and Information Sciences
(2019)
Arabic is recognised as the 4th most used language of the Internet. Arabic has three main varieties: (1) classical Arabic (CA), (2) Modern Standard Arabic (MSA), (3) Arabic Dialect (AD). MSA and AD could be written either in Arabic or in Ro...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.jksuci.2019.02.006
Helmut Schmid • International Conference on Computational Linguistics
(1994)
Text corpora which are tagged with part-of-speech information are useful in many areas of linguistic research. In this paper, a new part-of-speech tagging method based on neural networks (Net- Tagger) is presented and its performance is com...
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Open Access
DOI: https://doi.org/10.3115/991886.991915
Jianlin Cheng, Zheng Wang, Gianluca Pollastri • International Joint Conference on Neural Networks (IJCNN)
(2008)
Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional neural network to learn ordinal categories. Our approach is a gen...
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Open Access
DOI: https://doi.org/10.1109/ijcnn.2008.4633963
R. Daniel VanLuchene, ROUFEI SUN • Computer-Aided Civil and Infrastructure Engineering
(1990)
In the past few years literature on computational civil engineering has concentrated primarily on artificial intelligence (Al) applications involving expert system technology. This article discusses a different Al approach involving neural ...
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cc-by-nc-nd
DOI: https://doi.org/10.1111/j.1467-8667.1990.tb00377.x
W.D. Penny, David Frost • Medical Decision Making
(1996)
Neural networks are parallel, distributed, adaptive information-processing systems that develop their functionality in response to exposure to information. This paper is a tutorial for researchers intending to use neural nets for medical de...
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DOI: https://doi.org/10.1177/0272989x9601600409
Pooja Jain, Makarand Chintamani Deo • Ships and Offshore Structures
(2005)
The soft computing technique of neural network is being extensively used across all disciplines of ocean engineering, namely, offshore, coastal, and deep-ocean engineering including marine engineering. This paper takes a stock of the resear...
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DOI: https://doi.org/10.1533/saos.2004.0005
Richard J. Mammone (1994)
Neural Networks for speech processing. Neural Networks in the acquisition of speech by machine. The nervous system - fantasy and reality. Processing of complex stimuli in the mammalian cochlear nucleus. On the possible role of auditory peri...
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Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami et al. • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
(2019)
Representation learning in heterogeneous graphs aims to pursue a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This...
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Open Access
DOI: https://doi.org/10.1145/3292500.3330961
Stephan Rasp, Sebastian Lerch • Monthly Weather Review
(2018)
Abstract Ensemble weather predictions require statistical postprocessing of systematic errors to obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with distributional regression models in which the pa...
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other-oa
DOI: https://doi.org/10.1175/mwr-d-18-0187.1
• Choice Reviews Online
(1994)
At present, computers cannot think, make independent decisions, recognize visual and audible patterns, reach reliable conclusions without complete information or learn from their mistakes. The question this book and research into artificial...
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DOI: https://doi.org/10.5860/choice.32-2176
Hervé Abdi • Journal of Biological Systems
(1994)
Neural networks are composed of basic units somewhat analogous to neurons. These units are linked to each other by connections whose strength is modifiable as a result of a learning process or algorithm. Each of these units integrates indep...
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DOI: https://doi.org/10.1142/s0218339094000179
Mike Schuster, Kuldip K. Paliwal • IEEE Transactions on Signal Processing
(1997)
In the first part of this paper, a regular recurrent neural network (RNN) is extended to a bidirectional recurrent neural network (BRNN). The BRNN can be trained without the limitation of using input information just up to a preset future f...
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DOI: https://doi.org/10.1109/78.650093
Gavin Taylor • John Wiley & Sons, Inc. eBooks
(1996)
From the Publisher:
The chapters in this volume are an indication of the vigour and strength of the subject of neural networks in solving hard problems. They also indicate how the subject is giving new insights and developing new relations...
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Leon Ong Chua, Lei Yang • IEEE International Symposium on Circuits and Systems proceedings
(2003)
A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear circuits which process signals in real time. Like cellular automata, they are made of a massiv...
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DOI: https://doi.org/10.1109/iscas.1988.15089
Leon Ong Chua, L. Yang • IEEE Transactions on Circuits and Systems
(1988)
The theory of a novel class of information-processing systems, called cellular neural networks, which are capable of high-speed parallel signal processing, was presented in a previous paper (see ibid., vol.35, no.10, p.1257-72, 1988). A dyn...
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DOI: https://doi.org/10.1109/31.7601
Leon Ong Chua, L. Yang • IEEE Transactions on Circuits and Systems
(1988)
A novel class of information-processing systems called cellular neural networks is proposed. Like neural networks, they are large-scale nonlinear analog circuits that process signals in real time. Like cellular automata, they consist of a m...
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DOI: https://doi.org/10.1109/31.7600
Amey Thakur • International Journal for Research in Applied Science and Engineering Technology
(2021)
The purpose of this study is to familiarise the reader with the foundations of neural networks. Artificial Neural Networks (ANNs) are algorithm-based systems that are modelled after Biological Neural Networks (BNNs). Neural networks are an ...
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Open Access
DOI: https://doi.org/10.22214/ijraset.2021.37362
M. V. Altaĭsky • arXiv (Cornell University)
(2001)
It is suggested that a quantum neural network (QNN), a type of artificial neural network, can be built using the principles of quantum information processing. The input and output qubits in the QNN can be implemented by optical modes with d...
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Open Access
DOI: https://doi.org/10.48550/arxiv.quant-ph/0107012
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna et al. • arXiv (Cornell University)
(2013)
Deep neural networks are highly expressive models that have recently achieved state of the art performance on speech and visual recognition tasks. While their expressiveness is the reason they succeed, it also causes them to learn uninterpr...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1312.6199