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Academic Articles & Research Papers
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Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG et al. • Meitan kexue jishu
(2024)
The complex underground environment, filled with a large amount of dust and water vapor, and uneven illumination of artificial light source, leads to problems such as low illumination and loss of detail features in images collected by under...
DOAJ
Open Access (DOAJ)
DOI: 10.12438/cst.2023-1597
Kishan G. Mehrotra, Chilukuri Krishna Mohan, Sanjay Ranka • The MIT Press eBooks
(1996)
Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have ...
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DOI: https://doi.org/10.7551/mitpress/2687.001.0001
Ivan Sekaj, Ivan Kénický, Filip Zúbek • Mendel
(2021)
Artificial neural networks are means which are, among several other approaches, effectively usable for modelling and control of non-linear dynamic systems. In case of modelling systems input and output signals are a-priori known, supervised...
DOAJ
Open Access (DOAJ)
DOI: 10.13164/mendel.2021.2.007
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
Martin Anthony, Peter L. Bartlett • Cambridge University Press eBooks
(1999)
First published in 1999, this book describes theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. R...
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DOI: https://doi.org/10.1017/cbo9780511624216
Siwei Yu, Jianwei Ma • Reviews of Geophysics
(2021)
Abstract Recently deep learning (DL), as a new data‐driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the...
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DOI: https://doi.org/10.1029/2021rg000742
DeLiang Wang, Jitong Chen • IEEE/ACM Transactions on Audio Speech and Language Processing
(2018)
Speech separation is the task of separating target speech from background interference. Traditionally, speech separation is studied as a signal processing problem. A more recent approach formulates speech separation as a supervised learning...
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Open Access
DOI: https://doi.org/10.1109/taslp.2018.2842159
PMC: 6586438
Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi et al. • International Conference on Machine Learning and Applications
(2017)
Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an importan...
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Open Access
DOI: https://doi.org/10.1109/icmla.2017.0-134
Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics
(2019)
In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...
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DOI: https://doi.org/10.3390/electronics8030292
Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang et al. • IET Image Processing
(2022)
Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation us...
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DOI: https://doi.org/10.1049/ipr2.12419
Daichi Kando, Satoshi Tomioka, Naoki Miyamoto, Ryosuke Ueda • Applied Sciences
(2019)
In an optical measurement system using an interferometer, a phase extracting technique from interferogram is the key issue. When the object is varying in time, the Fourier-transform method is commonly used since this method can extract a ph...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app9173529
Yudong Zhang, Lijia Deng, Hengde Zhu, Wei Wang et al. • Information Fusion
(2023)
Integrating artificial intelligence with food category recognition has been a field of interest for research for the past few decades. It is potentially one of the next steps in revolutionizing human interaction with food. The modern advent...
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DOI: https://doi.org/10.1016/j.inffus.2023.101859
Maryam Mousaarab Najafabadi, Flavio Villanustre, Taghi M. Khoshgoftaar, Naeem Seliya et al. • Journal Of Big Data
(2015)
Abstract Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can con...
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DOI: https://doi.org/10.1186/s40537-014-0007-7
Luke de Oliveira • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
(2022)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07%282016%29069
Roger Alves de Oliveira, Math Bollen • Electric Power Systems Research
(2022)
This paper aims to introduce deep learning to the power quality community by reviewing the latest applications and discussing the open challenges of this technology. Publications covering deep learning to power quality are stratified in ter...
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DOI: https://doi.org/10.1016/j.epsr.2022.108887
Luke de Oliveira, Michael Kagan, Lester W. Mackey, Benjamin Philip Nachman et al. • Journal of High Energy Physics
(2016)
Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...
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DOI: https://doi.org/10.1007/jhep07(2016)069
Prot Piyakawanich, Pattarapong Phasukkit • Drones
(2024)
In the rapidly evolving domain of Unmanned Aerial Vehicles (UAVs), precise altitude estimation remains a significant challenge, particularly for lightweight UAVs. This research presents an innovative approach to enhance altitude estimation ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/drones8120718
Qiubo Zhong, Xiaoyi Fang • Journal of Electrical and Computer Engineering
(2021)
Loop closure detection serves as the fulcrum of improving the accuracy and precision in simultaneous localization and mapping (SLAM). The majority of loop detection methods extract artificial features, which fall short of learning comprehen...
DOAJ
Open Access (DOAJ)
DOI: 10.1155/2021/9978022
Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, Alexander J. McKeeken et al. • Methods in Ecology and Evolution
(2022)
Abstract Deep learning is driving recent advances behind many everyday technologies, including speech and image recognition, natural language processing and autonomous driving. It is also gaining popularity in biology, where it has been use...
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DOI: https://doi.org/10.1111/2041-210x.13901
John Cristian Borges Gamboa • arXiv (Cornell University)
(2017)
In many real-world application, e.g., speech recognition or sleep stage classification, data are captured over the course of time, constituting a Time-Series. Time-Series often contain temporal dependencies that cause two otherwise identica...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1701.01887