Results 31 to 40 of about 264,274 (268)
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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Deep Learning for Software Vulnerabilities Detection Using Code Metrics
IEEE Access, 2020 Software vulnerability can cause disastrous consequences for information security. Earlier detection of vulnerabilities minimizes these consequences.
Mohammed Zagane +2 more
doaj +1 more source
DL-MRI: A Unified Framework of Deep Learning-Based MRI Super Resolution [PDF]
Journal of Healthcare Engineering, 2021 Magnetic resonance imaging (MRI) is widely used in the detection and diagnosis of diseases. High-resolution MR images will help doctors to locate lesions and diagnose diseases. However, the acquisition of high-resolution MR images requires high magnetic field intensity and long scanning time, which will bring discomfort to patients and easily introduce
Huanyu Liu +4 more
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Demystifying Deep Learning: A Geometric Approach to Iterative Projections
, 2018 Parametric approaches to Learning, such as deep learning (DL), are highly popular in nonlinear regression, in spite of their extremely difficult training with their increasing complexity (e.g. number of layers in DL).
Dai, Liyi, Krim, Hamid, Panahi, Ashkan
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Insights into Imaging, 2023 Objective Develop and evaluate an ensemble clinical machine learning–deep learning (CML-DL) model integrating deep visual features and clinical data to improve the prediction of supraspinatus/infraspinatus tendon complex (SITC) injuries. Methods Patients
Yamuhanmode Alike +13 more
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BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning
, 2017 Understanding the global optimality in deep learning (DL) has been attracting more and more attention recently. Conventional DL solvers, however, have not been developed intentionally to seek for such global optimality.
Wang, Guanghui +2 more
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Alexandria Engineering Journal, 2023 Wireless Sensor Networks (WSNs) are widely studied for their data collection and monitoring capabilities across diverse applications. However, the limited energy resources of sensor nodes present a significant challenge in extending the network's ...
I. Surenther +2 more
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Deep Learning Solutions for TanDEM-X-based Forest Classification
, 2019 In the last few years, deep learning (DL) has been successfully and massively employed in computer vision for discriminative tasks, such as image classification or object detection.
Mazza, Antonio, Sica, Francescopaolo
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Deep Learning for Credit Card Fraud Detection: A Review of Algorithms, Challenges, and Solutions
IEEE AccessDeep learning (DL), a branch of machine learning (ML), is the core technology in today’s technological advancements and innovations. Deep learning-based approaches are the state-of-the-art methods used to analyse and detect complex patterns in ...
Ibomoiye Domor Mienye, Nobert Jere
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