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Now showing items 31-40 of 52
A New Benchmark Problem for Structural Damage Detection: Bolt Loosening Tests on a Large-Scale Laboratory Structure
(
Springer
, 2022 , Conference Paper)
Monitoring the structural performance of engineering structures has always been pertinent for maintaining structural health and assessing the life cycle of structures. Structural Health Monitoring (SHM) and Structural ...
Human experts vs. machines in taxa recognition
(
Elsevier B.V.
, 2020 , Article)
The step of expert taxa recognition currently slows down the response time of many bioassessments. Shifting to quicker and cheaper state-of-the-art machine learning approaches is still met with expert scepticism towards ...
Classification of polarimetric SAR images using compact convolutional neural networks
(
Bellwether Publishing, Ltd.
, 2021 , Article)
Classification of polarimetric synthetic aperture radar (PolSAR) images is an active research area with a major role in environmental applications. The traditional Machine Learning (ML) methods proposed in this domain ...
Real-Time Glaucoma Detection from Digital Fundus Images Using Self-ONNs
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Glaucoma leads to permanent vision disability by damaging the optical nerve that transmits visual images to the brain. The fact that glaucoma does not show any symptoms as it progresses and cannot be stopped at the later ...
One-Dimensional Convolutional Neural Networks for Real-Time Damage Detection of Rotating Machinery
(
Springer
, 2022 , Conference Paper)
This paper presents a novel real-time rotating machinery damage monitoring system. The system detects, quantifies, and localizes damage in ball bearings in a fast and accurate way using one-dimensional convolutional neural ...
Learned vs. hand-designed features for ECG beat classification: A comprehensive study
(
Springer Verlag
, 2017 , Conference Paper)
In this study, in order to find out the best ECG classification performance we realized comparative evaluations among the state-of-the-art classifiers such as Convolutional Neural Networks (CNNs), multi-layer perceptrons ...
Sleep stage classification using sparse rational decomposition of single channel EEG records
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
A sparse representation of ID signals is proposed based on time-frequency analysis using Generalized Rational Discrete Short Time Fourier Transform (RDSTFT). First, the signal is decomposed into a set of frequency sub-bands ...
Performance Comparison of Learned vs. Engineered Features for Polarimetric SAR Terrain Classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
In this work, we propose to use learned features for terrain classification of Polarimetric Synthetic Aperture Radar (PolSAR) images. In the proposed classification framework, the learned features are extracted from sliding ...
Face segmentation in thumbnail images by data-adaptive convolutional segmentation networks
(
IEEE Computer Society
, 2016 , Conference Paper)
In this study we address the problem of face segmentation in thumbnail images. While there have been several approaches for face detection, none performs detection in such low resolution and segmentation with pixel accuracy. ...
Generalized Operational Classifiers for Material Identification
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Material is one of the intrinsic features of objects, and consequently material recognition plays an important role in image understanding. The same material may have various shapes and appearance, while keeping the same ...