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Md Mijanur Rahman, Ashik Uzzaman, Sadia Islam Sami, Fatema Khatun et al. • IET Image Processing
(2024)
Abstract This study introduces a novel encoder–decoder framework based on deep neural networks and provides a thorough investigation into the field of automatic picture captioning systems. The suggested model uses a “long short‐term memory”...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/ipr2.13287
Zhong‐Qiu Zhao, Peng Zheng, Shou-Tao Xu, Xindong Wu • IEEE Transactions on Neural Networks and Learning Systems
(2019)
Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/tnnls.2018.2876865
Kevin Warburton • International Journal of Sustainability in Higher Education
(2003)
Deep learning is a key strategy by which students extract meaning and understanding from course materials and experiences. Because of the range and interconnectedness of environmental, social and economic issues, and the importance of inter...
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DOI: https://doi.org/10.1108/14676370310455332
Lei Zhang, Shuai Wang, Bing Liu • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
(2018)
Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state‐of‐the‐art prediction results. Along with the success of deep learning in many appl...
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Open Access
DOI: https://doi.org/10.1002/widm.1253
Aston Zhang, Zachary C. Lipton, Li Mu, Alexander Johannes Smola • arXiv (Cornell University)
(2021)
This open-source book represents our attempt to make deep learning approachable, teaching readers the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and...
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DOI: https://doi.org/10.48550/arxiv.2106.11342
Sandipan Sikdar, Rachneet Sachdeva, Johannes Wachs, Johannes Wachs et al. • Frontiers in Big Data
(2022)
This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fdata.2021.771404
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...
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Open Access
DOI: https://doi.org/10.1561/2000000039
François Chollet (2017)
DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. D...
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Samira Pouyanfar, Saad B Sadiq, Yilin Yan, Haiman Tian et al. • ACM Computing Surveys
(2018)
The field of machine learning is witnessing its golden era as deep learning slowly becomes the leader in this domain. Deep learning uses multiple layers to represent the abstractions of data to build computational models. Some key enabler d...
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DOI: https://doi.org/10.1145/3234150
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...
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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
Mohammed Javeed Zaki, Wagner Meira • Cambridge University Press eBooks
(2020)
The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...
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DOI: https://doi.org/10.1017/9781108564175
Simon J. Caton, Christian Stefan Haas • ACM Computing Surveys
(2023)
When Machine Learning technologies are used in contexts that affect citizens, companies as well as researchers need to be confident that there will not be any unexpected social implications, such as bias towards gender, ethnicity, and/or pe...
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DOI: https://doi.org/10.1145/3616865
Aishat I. Lepshakova, Oleg V. Kurskikh • Актуальные проблемы филологии и педагогической лингвистики
(2025)
The article analyses different translation versions of science fiction films directed by Denis Villeneuve with the aim of determining their semantic similarity through NLP analysis. There are four groups of metrics used in text analysis: se...
DOAJ
Open Access (DOAJ)
DOI: 10.29025/2079-6021-2025-1-132-150
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
Clara Muñoz-Castro, Ayush Noori, Colin G. Magdamo, Zhaozhi Li et al. • Journal of Neuroinflammation
(2022)
Abstract Background Astrocytes and microglia react to Aβ plaques, neurofibrillary tangles, and neurodegeneration in the Alzheimer’s disease (AD) brain. Single-nuclei and single-cell RNA-seq have revealed multiple states or subpopulations of...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12974-022-02383-4
William W. Hsieh • Cambridge University Press eBooks
(2009)
Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and th...
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DOI: https://doi.org/10.1017/cbo9780511627217
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...
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DOI: https://doi.org/10.1017/9781108690935
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...
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DOI: https://doi.org/10.5194/soil-6-35-2020
Andreas Müller, Sarah Guido (2016)
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teac...
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