Home »
Academic Articles & Research Papers
Showing 20 of 1,578 academic articles
Li Deng, Dong Yu • Foundations and Trends® in Signal Processing
(2014)
This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise...
OPENALEX
Open Access
DOI: https://doi.org/10.1561/2000000039
John D. Kelleher • The MIT Press eBooks
(2019)
An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vi...
OPENALEX
DOI: https://doi.org/10.7551/mitpress/11171.001.0001
Seonwoo Min, Byunghan Lee, Sungroh Yoon • Briefings in Bioinformatics
(2016)
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-th...
OPENALEX
Open Access
DOI: https://doi.org/10.1093/bib/bbw068
Ian Goodfellow, Yoshua Bengio, Aaron C. Courville • The MIT Press eBooks
(2016)
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...
OPENALEX
DOI: https://doi.org/10.1016/b978-0-12-804291-5.00010-6
Gabriel de Sousa Meira, João Victor Ferreira Guedes, Edilson de Souza Bias • Drones
(2024)
The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/drones8070341
Daniel Kirk, E.J. Kok, Michele Tufano, Bedir Teki̇nerdoğan et al. • Advances in Nutrition
(2022)
Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and ...
OPENALEX
cc-by-nc
DOI: https://doi.org/10.1093/advances/nmac103
PMC: 9776646
Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access
(2024)
The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...
OPENALEX
cc-by
DOI: https://doi.org/10.1109/access.2024.3365349
Max Mowbray, Thomas Savage, Chufan Wu, Ziqi Song et al. • Biochemical Engineering Journal
(2021)
The field of machine learning is comprised of techniques, which have proven powerful approaches to knowledge discovery and construction of ‘digital twins’ in the highly dimensional, nonlinear and stochastic domains common to biochemical eng...
OPENALEX
cc-by
DOI: https://doi.org/10.1016/j.bej.2021.108054
Róbert Skapinyecz • Machine Learning and Knowledge Extraction
(2026)
The paper presents a novel large language model-based neighbourhood search method for production scheduling using discrete-event simulation (DES) as the modelling and evaluation engine. The combination of large language models (LLMs) and DE...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/make8090284
Jeremy M. Watt, Reza Borhani, Aggelos K. Katsaggelos • Cambridge University Press eBooks
(2020)
With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuiti...
OPENALEX
DOI: https://doi.org/10.1017/9781108690935
Jichao Li, Xiaosong Du, Joaquim R. R. A. Martins • Progress in Aerospace Sciences
(2022)
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and pr...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1016/j.paerosci.2022.100849
Artur M. Schweidtmann, Erik Esche, Asja Fischer, Marius Kloft et al. • Chemie Ingenieur Technik
(2021)
Abstract The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio‐)catalysts, and functional materials. Recent breakthroughs in machine learning (ML)...
OPENALEX
cc-by
DOI: https://doi.org/10.1002/cite.202100083
José Padarian, Budiman Minasny, Alex B. McBratney • SOIL
(2020)
Abstract. The application of machine learning (ML) techniques in various fields of science has increased rapidly, especially in the last ten years. The increasing availability of soil data that can be efficiently acquired remotely and proxi...
OPENALEX
cc-by
DOI: https://doi.org/10.5194/soil-6-35-2020
Yitu Fu, Ju Xu • IEEE Access
(2019)
In this paper, we model the malware detection problem as a graph inference problem, and develop a novel belief propagation approach within a semi-supervised learning scheme that fully makes use of files' and hosts' connections to detect mal...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2948374
Ioannis Kavakiotis, O. Tsave, Athanasios Salifoglou, Nicos Maglaveras et al. • Computational and Structural Biotechnology Journal
(2017)
The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, ap...
OPENALEX
cc-by
DOI: https://doi.org/10.1016/j.csbj.2016.12.005
PMC: 5257026
Orges Koci, Richard K. Russell, M. Guftar Shaikh, Christine Edwards et al. • Microbiome
(2024)
Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40168-024-01834-9
Raymund C. Sison, Masamichi Shimura (1998)
After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge neces...
OPENALEX
Open Access
Qingyang Ling • Applied and Computational Engineering
(2023)
Machine learning is a field of study where the computer can learn for itself without a human explicitly hardcoding the knowledge for it. These algorithms make up the backbone of machine learning. This paper aims to study the field of machin...
OPENALEX
cc-by
DOI: https://doi.org/10.54254/2755-2721/4/20230355
Pedro Domingos • Communications of the ACM
(2012)
Tapping into the "folk knowledge" needed to advance machine learning applications....
OPENALEX
DOI: https://doi.org/10.1145/2347736.2347755
Kostiantyn Fuks • Green, Blue and Digital Economy Journal
(2024)
The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysi...
DOAJ
Open Access (DOAJ)
DOI: 10.30525/2661-5169/2024-1-4