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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
Peter R. Wiecha, Arnaud Arbouet, Christian Girard, Otto L. Muskens • Photonics Research
(2021)
Deep learning in the context of nano-photonics is mostly discussed in terms of its potential for inverse design of photonic devices or nano-structures. Many of the recent works on machine-learning inverse design are highly specific, and the...
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Open Access
DOI: https://doi.org/10.1364/prj.415960
Anindya Gupta, Philip John Harrison, Håkan Wieslander, Nicolas Pielawski et al. • Cytometry Part A
(2018)
Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and ho...
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cc-by-nc
DOI: https://doi.org/10.1002/cyto.a.23701
PMC: 6590257
Leon Herrmann, Stefan Kollmannsberger • Computational Mechanics
(2024)
Abstract The rapid growth of deep learning research, including within the field of computational mechanics, has resulted in an extensive and diverse body of literature. To help researchers identify key concepts and promising methodologies w...
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DOI: https://doi.org/10.1007/s00466-023-02434-4
Dulani Meedeniya • Chapman & Hall/CRC eBooks
(2023)
This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....
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public-domain
DOI: https://doi.org/10.1201/9781003390824
Mecit Kantarcı, Volkan Kızılgöz, Ramazan Terzi, Ahmet Enes Kılıç et al. • Diagnostic and Interventional Radiology
(2025)
PURPOSE: This study aimed to evaluate the effectiveness of artificial intelligence (AI) in diagnosing focal nodular hyperplasia (FNH) of the liver using magnetic resonance imaging (MRI) and compare its performance with that of radiologists....
DOAJ
Open Access (DOAJ)
DOI: 10.4274/dir.2025.243095
Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences
(2025)
In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15031552
Xiaoxiao Ma, Jia Xin Wu, Shan Xue, Jian Yu Yang et al. • IEEE Transactions on Knowledge and Data Engineering
(2021)
Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...
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Open Access
DOI: https://doi.org/10.1109/tkde.2021.3118815
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
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
Ardian Kelmendi, George Pappas • Algorithms
(2025)
The automotive industry increasingly relies on 3D modeling technologies to design and manufacture vehicle components with high precision. One critical challenge is optimizing the placement of latches that secure the dashboard side paneling,...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/a18090553
Haohan Wang, Bhiksha Raj • arXiv (Cornell University)
(2017)
This paper is a review of the evolutionary history of deep learning models. It covers from the genesis of neural networks when associationism modeling of the brain is studied, to the models that dominate the last decade of research in deep ...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1702.07800
Wataru Imai, Masaaki Ikehara • IEEE Access
(2022)
Under severe weather conditions, the quality of the images taken outside is directly affected by floating atmospheric particles. To keep the quality of the images, haze removal methods play a critical role. The most difficult part of haze r...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2022.3204026
Boris Galitsky • Entropy
(2023)
It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/e25111496
Yoon Joo Choi, Sujeong Han, Chena Lee, Kug Jin Jeon et al. • Scientific Reports
(2026)
Abstract The inferior alveolar nerve (IAN) is the major sensory nerve innervating the mandibular region, and its automatic segmentation is crucial. It has been indirectly identified on the mandibular canal, which surrounds the IAN, using co...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-026-45392-6
Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics
(2020)
Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.pacs.2020.100215
PMC: 7779783
• 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
Navin Kumar Manaswi • Apress eBooks
(2018)
This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such ...
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DOI: https://doi.org/10.1007/978-1-4842-3516-4
JongCheol Pyo, Hongtao Duan, Mayzonee Ligaray, Minjeong Kim et al. • Remote Sensing
(2020)
Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estim...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs12071073
Sara Sheehan, Yun S. Song • PLoS Computational Biology
(2016)
Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep...
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DOI: https://doi.org/10.1371/journal.pcbi.1004845
PMC: 4809617