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Academic Articles & Research Papers
Showing 20 of 594 academic articles
Kai Chen, Pengtao Zhang, Liang You, Jian Sun • Applied Sciences
(2024)
In response to the challenge of single navigation methods failing to meet the high precision requirements for unmanned aerial vehicle (UAV) navigation in complex environments, a novel algorithm that integrates Global Navigation Satellite Sy...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app14135493
RT Pramod, Michael A Cohen, Joshua B Tenenbaum, Nancy Kanwisher • eLife
(2022)
Successful engagement with the world requires the ability to predict what will happen next. Here, we investigate how the brain makes a fundamental prediction about the physical world: whether the situation in front of us is stable, and henc...
DOAJ
Open Access (DOAJ)
DOI: 10.7554/eLife.71736
Ben Kröse, Ben Kröse, Patrick van der Smagt, Patrick van der Smagt (1993)
Contents Preface 9 I FUNDAMENTALS 11 1 Introduction 13 2 Fundamentals 15 2.1 A framework for distributed representation : : : : : : : : : : : : : : : : : : : : : 15 2.1.1 Processing units : : : : : : : : : : : : : : : : : : : : : : : : : : ...
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Xin Yao • Proceedings of the IEEE
(1999)
Learning and evolution are two fundamental forms of adaptation. There has been a great interest in combining learning and evolution with artificial neural networks (ANNs) in recent years. This paper: 1) reviews different combinations betwee...
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DOI: https://doi.org/10.1109/5.784219
Edmund T. Rolls, Alessandro Treves • Oxford University Press eBooks
(1997)
The aim of this book is to describe the types of computation that can be performed by biologically plausible neural networks, and to show how these may be implemented in different systems in the brain. The book is structured in three sectio...
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DOI: https://doi.org/10.1093/acprof:oso/9780198524328.001.0001
Ajith Abraham • Wiley eBooks
(2005)
Abstract Artificial neural networks are useful tools that have been applied successfully in a broad range of signal‐processing problems. From a signal‐processing perspective, their ability to adapt continuously to new data allows them to tr...
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DOI: https://doi.org/10.1002/0471497398.mm421
Keiron O’Shea, Ryan Nash • arXiv (Cornell University)
(2015)
The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of art...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1511.08458
Mohamad H. Hassoun • Proceedings of the IEEE
(1996)
From the Publisher:
As book review editor of the IEEE Transactions on Neural Networks, Mohamad Hassoun has had the opportunity to assess the multitude of books on artificial neural networks that have appeared in recent years. Now, in Funda...
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DOI: https://doi.org/10.1109/jproc.1996.503146
Vijayamanikandan Vijayarangan, Harshavardhana A. Uranakara, Francisco E. Hernández–Pérez, Hong G. Im • Energy and AI
(2025)
Using information theory, this study provides insights into how the construction of latent space of autoencoder (AE) using deep neural network (DNN) training finds a smooth (non-stiff) low-dimensional manifold in the stiff dynamical system....
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.egyai.2025.100567
P. V. Chandrika, Sandeep Kelkar • Advances in medical diagnosis, treatment, and care (AMDTC) book series
(2024)
This chapter deals with the basic understanding of the deep learning model. It starts with a view of artificial intelligence, machine learning, and deep learning. It also represents how these three concepts are related to each other. The en...
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DOI: https://doi.org/10.4018/979-8-3693-1281-0.ch001
Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, Lúcio André de Castro Jorge et al. • International Journal of Applied Earth Observation and Geoinformation
(2021)
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, ...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.jag.2021.102456
Roberto De Fazio, Matteo Paiano, Ramiro Velazquez, Carolina Del-Valle-Soto et al. • Applied Sciences
(2026)
Automatic sleep staging is fundamental for diagnosing sleep disorders and enabling long-term sleep monitoring with wearable devices. Although Deep Learning has significantly improved classification performance, balancing accuracy with compu...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app16168164
• De Gruyter eBooks
(2020)
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...
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DOI: https://doi.org/10.1515/9783110670905
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Shrooq Alsenan, Isra Al-Turaiki, Alaaeldin Hafez • PeerJ Computer Science
(2021)
The blood–brain barrier plays a crucial role in regulating the passage of 98% of the compounds that enter the central nervous system (CNS). Compounds with high permeability must be identified to enable the synthesis of brain medications for...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj-cs.515
S. Suganyadevi, V. Seethalakshmi, K. Balasamy • International Journal of Multimedia Information Retrieval
(2021)
Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the quickest developing field in artificial intelligence and is ef...
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other-oa
DOI: https://doi.org/10.1007/s13735-021-00218-1
PMC: 8417661
Massimiliano Luca, Gianni Barlacchi, Bruno Lepri, Luca Pappalardo • ACM Computing Surveys
(2021)
The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS t...
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Open Access
DOI: https://doi.org/10.1145/3485125
Gustau Camps‐Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein • Wiley eBooks
(2021)
Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...
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Open Access
DOI: https://doi.org/10.1002/9781119646181
Jan Kukačka, Vladimir Golkov, Daniel Cremers • arXiv (Cornell University)
(2017)
Regularization is one of the crucial ingredients of deep learning, yet the term regularization has various definitions, and regularization methods are often studied separately from each other. In our work we present a systematic, unifying t...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1710.10686
Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth et al. • International Journal of Computer Vision
(2019)
Abstract Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined categories in natural images. Deep learning techniques have emerged as a ...
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DOI: https://doi.org/10.1007/s11263-019-01247-4