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Academic Articles & Research Papers
Showing 20 of 58 academic articles
Didit Adytia, Dede Tarwidi, Deni Saepudin, Semeidi Husrin et al. • MethodsX
(2024)
The goal of this research is to develop a model employing deep neural networks (DNNs) to predict the effectiveness of mangrove forests in attenuating the impact of tsunami waves. The dataset for the DNN model is obtained by simulating tsuna...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.mex.2024.102791
Jian HUANG, Xin LI, Fang CHEN, Ru CUI et al. • Zhongguo dizhi zaihai yu fangzhi xuebao
(2022)
The traditional high-level remote landslide recognition efficiency which relies on the artificial discrimination of geological experts is low. In this paper, an automatic landslide terrain recognition model based on deep learning is develop...
DOAJ
Open Access (DOAJ)
DOI: 10.16031/j.cnki.issn.1003-8035.2022.02-05
Caricato A., Ficarella A., Chiodo L. Spada • E3S Web of Conferences
(2021)
Predictive maintenance is the latest frontier in the management and maintenance of many industrial assets, including aeroengines. Made possible by last decades advances in monitoring equipment and machine learning algorithms, it permits ind...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/e3sconf/202131211017
Yashar Bashirzadeh, Hossein Moghimianavval, Allen P. Liu • iScience
(2022)
Summary: Cell shape changes from locomotion to cytokinesis are, to a large extent, driven by myosin-driven remodeling of cortical actin patterns. Passive crosslinkers such as α-actinin and fascin as well as actin nucleator Arp2/3 complex la...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.isci.2022.104236
Felicia A. Hardi, Leigh G. Goetschius, Scott Tillem, Vonnie McLoyd et al. • Developmental Cognitive Neuroscience
(2023)
Unstable and unpredictable environments are linked to risk for psychopathology, but the underlying neural mechanisms that explain how instability relate to subsequent mental health concerns remain unclear. In particular, few studies have fo...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.dcn.2023.101253
Chao He, Ruyan Wang • Sensors
(2020)
Integrated fiber-wireless (FiWi) should be regarded as a promising access network architecture in future 5G networks, and beyond; this due to its seamless combination of flexibility, ubiquity, mobility of the wireless mesh network (WMN) fro...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s20133794
Raviraju Balappa D, Gautam Kumar Rajput • Shodh Sari
(2025)
Matrices are foundational to artificial intelligence (AI), serving as critical tools for data representation, manipulation, and transformation across various applications. From machine learning algorithms to neural network architectures, ma...
DOAJ
Open Access (DOAJ)
DOI: https://doi.org/10.59231/SARI7840
Uwe Glässer, Yuri G. Gurevich, Margus Veanes • IEEE Transactions on Software Engineering
(2004)
In some distributed and mobile communication models, a message disappears in one place and miraculously appears in another. In reality, of course, there are no miracles. A message goes from one network to another; it can be lost or corrupte...
OPENALEX
DOI: https://doi.org/10.1109/tse.2004.25
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 ...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1162/coli_r_00312
George N. Bebis, Michael Georgiopoulos • IEEE Potentials
(1994)
One critical aspect neural network designers face today is choosing an appropriate network size for a given application. Network size involves in the case of layered neural network architectures, the number of layers in a network, the numbe...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/45.329294
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
T. Sorsa, Heikki N. Koivo, Hannu J. Koivisto • IEEE Transactions on Systems Man and Cybernetics
(1991)
Fault detection and diagnosis is an important problem in process automation. Both model-based methods and expert systems have been suggested to solve the problem, along with the pattern recognition approach. A number of possible neural netw...
OPENALEX
DOI: https://doi.org/10.1109/21.108299
Omid M. Omidvar • Ablex Pub. Corp. eBooks
(1991)
Receptive field calculus, Jan J. Koenderink visual reconstruction and data fusion, D. Suter visual perception of translational and rotational motion, Jim-Shih Liaw, Irwin K. King and Michael A. Arbib neural network for recovering observer m...
OPENALEX
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...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3292500.3330961
Maximilian Alber, Sebastian Lapuschkin, Philipp Seegerer, Miriam Hägele et al. • arXiv (Cornell University)
(2018)
In recent years, deep neural networks have revolutionized many application domains of machine learning and are key components of many critical decision or predictive processes. Therefore, it is crucial that domain specialists can understand...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1808.04260
J. Lee, Ronald C. Weger, S.K. Sengupta, Ronald M. Welch • IEEE Transactions on Geoscience and Remote Sensing
(1990)
It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery ...
OPENALEX
DOI: https://doi.org/10.1109/36.58972
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...
OPENALEX
DOI: https://doi.org/10.4018/978-1-5225-7368-5.ch004
Bing Cheng, D. Michael Titterington • Statistical Science
(1994)
This paper informs a statistical readership about Artificial Neural Networks (ANNs), points out some of the links with statistical methodology and encourages cross-disciplinary research in the directions most likely to bear fruit. The areas...
OPENALEX
Open Access
DOI: https://doi.org/10.1214/ss/1177010638
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...
OPENALEX
DOI: https://doi.org/10.1061/(asce)0733-9364(1991)117:4(606)
Hecht-Nielsen • International Joint Conference on Neural Networks (IJCNN)
(1989)
The author presents a survey of the basic theory of the backpropagation neural network architecture covering architectural design, performance measurement, function approximation capability, and learning. The survey includes previously know...
OPENALEX
DOI: https://doi.org/10.1109/ijcnn.1989.118638