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Showing 20 of 4,247 academic articles
Sandhya Samarasinghe • Auerbach Publications eBooks
(2011)
In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introd...
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DOI: https://doi.org/10.1201/9780849333750
Kyoung-Mi Jang, Myung-Sun Kim, Do-Won Kim • Frontiers in Human Neuroscience
(2020)
This study investigated deficits of spatial working memory in college students with attention-deficit/hyperactivity disorder (ADHD) traits using event-related potentials (ERPs) and the spatial 2-back task. We also computed sensory-level act...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fnhum.2020.580813
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
Giulio Bondanelli, Thomas Deneux, Brice Bathellier, Srdjan Ostojic • eLife
(2021)
Across sensory systems, complex spatio-temporal patterns of neural activity arise following the onset (ON) and offset (OFF) of stimuli. While ON responses have been widely studied, the mechanisms generating OFF responses in cortical areas h...
DOAJ
Open Access (DOAJ)
DOI: 10.7554/eLife.53151
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
Kevin M. Swingler (1996)
Techniques for building neural networks: introduction what are neural networks? how does neural computing differ from traditional programming? how are neural networks built? how do neural networks learn? what do I need to build an MLP? the ...
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Qi‐Jun Zhang, K.C. Gupta • Artech House, Inc. eBooks
(2000)
From the Publisher:
Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks information processing systems that can learn, generalize, and even allow model developm...
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Filippo Amato, Alberto Botana López, Eladia María Peña‐Méndez, Petr Vaňhara et al. • Journal of Applied Biomedicine
(2013)
An extensive amount of information is currently available to clinical specialists, ranging from details of clinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of data provides information that mu...
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Open Access
DOI: https://doi.org/10.2478/v10136-012-0031-x
Kevin L. Priddy, Paul E. Keller • SPIE eBooks
(2005)
This tutorial text provides the reader with an understanding of artificial neural networks (ANNs) and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed and th...
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DOI: https://doi.org/10.1117/3.633187
Marcus D. Odom, Ramesh Sharda • International Joint Conference on Neural Networks (IJCNN)
(1990)
A neural network model is developed for prediction of bankruptcy, and it is tested using financial data from various companies. The same set of data is analyzed using a more traditional method of bankruptcy prediction, multivariate discrimi...
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DOI: https://doi.org/10.1109/ijcnn.1990.137710
Holger Schwenk, Yoshua Bengio • Neural Computation
(2000)
Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, AdaBoost, has been applied with great success to several benchmark machine learning problems using mainly decision tr...
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DOI: https://doi.org/10.1162/089976600300015178
John Hancock, Taghi M. Khoshgoftaar • Journal Of Big Data
(2020)
Abstract This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known. However, researchers continue to discover n...
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cc-by
DOI: https://doi.org/10.1186/s40537-020-00305-w
Juan F. Saldarriaga, Fabio Freire, Jose Freire • Chemical Engineering Transactions
(2018)
The minimum spouting velocity is one of the fundamental parameters in the application of the conical spouted bed pyrolysis, gasification and combustion, therefore it is necessary the adequate calculation and the use of a correlation with go...
DOAJ
Open Access (DOAJ)
DOI: 10.3303/CET1870208
Florence Choong Chiao Mei, Bryan Ng Jan Hong • Journal of Engineering Technology and Applied Physics
(2025)
Agriculture is one of the largest sectors that contribute to the economic growth of countries, including Malaysia. However, plant diseases affect the quality of the harvest and impede farmers’ maximum yield output. Therefore, early detectio...
DOAJ
Open Access (DOAJ)
DOI: 10.33093/jetap.2025.7.1.2
Ivana Valentina Lemmuela, Mewati Ayub, Oscar Karnalim • Journal of Information Systems Engineering and Business Intelligence
(2025)
Background: Communication is important for everyone, including individuals with hearing and speech impairments. For this demographic, sign language is widely used as the primary medium of communication with others who share similar conditio...
DOAJ
Open Access (DOAJ)
DOI: 10.20473/jisebi.11.1.17-29
P. Jagadesh, J. Harshini, D. Arul, Solomon Oyebisi et al. • Discover Civil Engineering
(2026)
Abstract This study predicts the Air Quality Index (AQI) in the Coimbatore region using Artificial Neural Networks (ANN) to enhance air quality management and environmental science. The researchers measured six input variables over a two-ye...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44290-026-00423-z
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
Peter M. Atkinson, Adrian R. L. Tatnall • International Journal of Remote Sensing
(1997)
Abstract. Over the past decade there have been considerable increases in both the quantity of remotely sensed data available and the use of neural networks. These increases have largely taken place in parallel, and it is only recently that ...
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DOI: https://doi.org/10.1080/014311697218700
Qingyang Xiao, Kaiyuan Liu, Yuhui Hong, Haixu Tang • ACS in focus
(2024)
In recent years, breakthroughs in artificial intelligence (AI) have dramatically transformed many fields. Developments in neural networks primarily drive the advances. These powerful models have demonstrated unprecedented capabilities in le...
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DOI: https://doi.org/10.1021/acsinfocus.7e8012
Uihoon Jung, Miseong Kim, Jaewon Jang, Jin‐Hyuk Bae et al. • Advanced Science
(2024)
Abstract With increasing demand for wearable electronics capable of computing huge data, flexible neuromorphic systems mimicking brain functions have been receiving much attention. Despite considerable efforts in developing practical neural...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/advs.202307494