Home »
Academic Articles & Research Papers
Showing 20 of 864 academic articles
• IGI Global eBooks
(2004)
Neural Network is defined as the ability of a group to solve more problems than its individual members.The idea brings that a group of people can solve problems efficiently and offer greater insight and a better answer than any one individu...
OPENALEX
DOI: https://doi.org/10.4018/978-1-59140-176-6
Yu Zhang, Peter Tiňo B, Aleš Leonardis, Ke Tang • IEEE Transactions on Emerging Topics in Computational Intelligence
(2021)
Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's trust on deep learning systems. It is also related to many ethical problems, e.g.,...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tetci.2021.3100641
Lotfi A. Zadeh • Communications of the ACM
(1994)
article Free Access Share on Fuzzy logic, neural networks, and soft computing Author: Lotfi A. Zadeh Univ. of California, Berkeley Univ. of California, BerkeleyView Profile Authors Info & Claims Communications of the ACMVolume 37Issue 3Marc...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/175247.175255
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...
OPENALEX
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...
OPENALEX
DOI: https://doi.org/10.1080/17460441.2016.1201262
Martin Sundermeyer, Ralf Schlüter, Hermann Ney • Interspeech (USB)
(2012)
Neural networks have become increasingly popular for the task of language modeling.Whereas feed-forward networks only exploit a fixed context length to predict the next word of a sequence, conceptually, standard recurrent neural networks ca...
OPENALEX
Open Access
DOI: https://doi.org/10.21437/interspeech.2012-65
Binh‐Son Hua, Minh-Khoi Tran, Sai-Kit Yeung • IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
(2018)
Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored....
OPENALEX
Open Access
DOI: https://doi.org/10.1109/cvpr.2018.00109
R. Glen Donaldson, Mark J. Kamstra • Journal of Forecasting
(1996)
This paper investigates the use of Artificial Neural Networks (ANNs) to combine time series forecasts of stock market volatility from the USA, Canada, Japan and the UK. We demonstrate that combining with nonlinear ANNs generally produces fo...
OPENALEX
DOI: https://doi.org/10.1002/(sici)1099-131x(199601)15:1<49::aid-for604>3.0.co;2-2
Mikhail Yurochkin, Mayank Agarwal, Ghosh, Soumya, Kristjan H. Greenewald et al. • arXiv (Cornell University)
(2019)
In federated learning problems, data is scattered across different servers and exchanging or pooling it is often impractical or prohibited. We develop a Bayesian nonparametric framework for federated learning with neural networks. Each data...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1905.12022
Vivek Prakash Nigam, Daniel Graupe • Neurological Research
(2004)
Diagnosis of epilepsy is primarily based on scalp-recorded electroencephalograms (EEG). Unfortunately the long-term recordings obtained from 'ambulatory recording systems' contain EEG data of up to one week duration, which has introduced ne...
OPENALEX
DOI: https://doi.org/10.1179/016164104773026534
Tommy W. S. Chow, Siu‐Yeung Cho • Series in electrical and computer engineering
(2007)
This book covers neural networks with special emphasis on advanced learning methodologies and applications. It includes practical issues of weight initializations, stalling of learning, and escape from a local minima, which have not been co...
OPENALEX
DOI: https://doi.org/10.1142/p487
Tim Hill, Marcus J. O’Connor, William Remus • Management Science
(1996)
Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series ...
OPENALEX
DOI: https://doi.org/10.1287/mnsc.42.7.1082
Qeethara Kadhim Al-Shayea (2011)
Artificial neural networks are finding many uses in the medical diagnosis application. The goal of this paper is to evaluate artificial neural network in disease diagnosis. Two cases are studied. The first one is acute nephritis disease; da...
OPENALEX
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...
OPENALEX
DOI: https://doi.org/10.1109/52.143107
Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler et al. • arXiv (Cornell University)
(2018)
Neural networks are known to be a class of highly expressive functions able to fit even random input-output mappings with $100\%$ accuracy. In this work, we present properties of neural networks that complement this aspect of expressivity. ...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1806.08734
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...
OPENALEX
DOI: https://doi.org/10.1177/0272989x9601600409
Pierre Baldi, Yves Chauvin • Neural Computation
(1993)
After collecting a data base of fingerprint images, we design a neural network algorithm for fingerprint recognition. When presented with a pair of fingerprint images, the algorithm outputs an estimate of the probability that the two images...
OPENALEX
DOI: https://doi.org/10.1162/neco.1993.5.3.402
Hongsik Jeong, Luping Shi • Journal of Physics D Applied Physics
(2018)
Abstract Neural network technologies have taken center stage owing to their powerful computing capability for supporting deep learning in artificial intelligence. However, conventional synaptic devices such as SRAM and DRAM are not satisfac...
OPENALEX
cc-by
DOI: https://doi.org/10.1088/1361-6463/aae223
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...
OPENALEX
DOI: https://doi.org/10.1533/saos.2004.0005
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...
OPENALEX