Modeling, diagnostics, optimization, and control of internal combustion engines via modern machine learning techniques: A review and future directions
A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …
High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning
High-dimensional problem domains pose significant challenges for anomaly detection. The
presence of irrelevant features can conceal the presence of anomalies. This problem, known …
presence of irrelevant features can conceal the presence of anomalies. This problem, known …
Involvement of machine learning for breast cancer image classification: a survey
AA Nahid, Y Kong - Computational and mathematical methods …, 2017 - Wiley Online Library
Breast cancer is one of the largest causes of women's death in the world today. Advance
engineering of natural image classification techniques and Artificial Intelligence methods …
engineering of natural image classification techniques and Artificial Intelligence methods …
Ensembles of deep learning architectures for the early diagnosis of the Alzheimer's disease
Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of
Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be …
Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be …
[PDF][PDF] Survey on neural network architectures with deep learning
S Smys, JIZ Chen, S Shakya - Journal of Soft Computing Paradigm …, 2020 - academia.edu
In the present research era, machine learning is an important and unavoidable zone where
it provides better solutions to various domains. In particular deep learning is one of the cost …
it provides better solutions to various domains. In particular deep learning is one of the cost …
Stacked sparse autoencoder-based deep network for fault diagnosis of rotating machinery
As a breakthrough in the field of machine fault diagnosis, deep learning has great potential
to extract more abstract and discriminative features automatically without much prior …
to extract more abstract and discriminative features automatically without much prior …
Maximum entropy scaled super pixels segmentation for multi-object detection and scene recognition via deep belief network
Recent advances in visionary technologies impacted multi-object recognition and scene
understanding. Such scene-understanding tasks are a demanding part of several …
understanding. Such scene-understanding tasks are a demanding part of several …
An efficient feature generation approach based on deep learning and feature selection techniques for traffic classification
H Shi, H Li, D Zhang, C Cheng, X Cao - Computer Networks, 2018 - Elsevier
Substantial recent efforts have been made on the application of Machine Learning (ML)
techniques to flow statistical features for traffic classification. However, the classification …
techniques to flow statistical features for traffic classification. However, the classification …
Visual recognition based on deep learning for navigation mark classification
M Pan, Y Liu, J Cao, Y Li, C Li, CH Chen - IEEE Access, 2020 - ieeexplore.ieee.org
Recognizing objects from camera images is an important field for researching smart ships
and intelligent navigation. In sea transportation, navigation marks indicating the features of …
and intelligent navigation. In sea transportation, navigation marks indicating the features of …
Discriminative deep belief networks with ant colony optimization for health status assessment of machine
On-line health status monitoring, a key part of prognostics and health management, provides
various benefits, such as preventing unexpected failure and improving safety and reliability …
various benefits, such as preventing unexpected failure and improving safety and reliability …