Results 31 to 40 of about 267,347 (270)
Deep learning: Applications, architectures, models, tools, and frameworks: A comprehensive survey
CAAI Transactions on Intelligence Technology, 2023 Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting new knowledge. By using DL, the extraction of advanced data representations and knowledge can be made possible.
Mehdi Gheisari +10 more
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Deep learning methods may not outperform other machine learning methods on analyzing genomic studies
Frontiers in Genetics, 2022 Deep Learning (DL) has been broadly applied to solve big data problems in biomedical fields, which is most successful in image processing. Recently, many DL methods have been applied to analyze genomic studies. However, genomic data usually has too small
Yao Dong +11 more
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IEEE Access, 2023 As deep learning applications are getting popular in embedded systems, how to support deep learning applications in the model-based embedded software design methodology becomes a challenging problem. A previous solution is to represent each deep learning
Jangryul Kim, Jaewoo Son, Soonhoi Ha
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Review of intrusion detection systems based on deep learning techniques: coherent taxonomy, challenges, motivations, recommendations, substantial analysis and future directions [PDF]
, 2004 This study reviews and analyses the research landscape for intrusion detection systems (IDSs) based on deep learning (DL) techniques into a coherent taxonomy and identifies the gap in this pivotal research area.
Aleesa, A. M. +3 more
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WARC-DL: Scalable Web Archive Processing for Deep Learning
, 2022 Submitted to OSSYM 2022 - 4th International Open Search ...
Deckers, Niklas, Potthast, Martin
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A Comparative Study of Deep Learning and Traditional Methods for Environmental Remote Sensing [PDF]
ITM Web of Conferences, 2023 Because of the accessibility of massive data from remote sensing data and developments in ML, machine learning (ML) techniques have been extensively applied in environmental remote sensing research.
Farooq Bazila, Manocha Ankush
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, 2023 Deep learning (DL) is a highly impactful field in machine learning that has revolutionized various domains. DL can learn from large datasets, extract complex patterns, and make accurate predictions. It has applications in computer vision, natural language processing, healthcare, finance, and more.
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Nature Communications, 2021 Recent critical commentaries unfavorably compare deep learning (DL) with standard machine learning (SML) for brain imaging data analysis. Here, the authors show that if trained following prevalent DL practices, DL methods substantially improve compared ...
Anees Abrol +6 more
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DL-Reg: A Deep Learning Regularization Technique using Linear Regression
, 2020 Regularization plays a vital role in the context of deep learning by preventing deep neural networks from the danger of overfitting. This paper proposes a novel deep learning regularization method named as DL-Reg, which carefully reduces the nonlinearity of deep networks to a certain extent by explicitly enforcing the network to behave as much linear ...
Dialameh, Maryam +2 more
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Deep Learning (DL) approaches in Orthopedics: A Literature Review
, 2021 {"references": ["1.\tBjarnadottir, Ragnhildur I., et al. \"Implementation of electronic health records in US nursing homes.\" Computers, informatics, nursing: CIN 35.8 (2017): 417.", "2.\tTan, Zhiqiang, et al. \"An Automatic Classification Method for Adolescent Idiopathic Scoliosis Based on U-net and Support Vector Machine.\" Journal of Imaging Science
Dr. Fahad Siddique Jatoi +2 more
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