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Now showing items 21-30 of 40
1D convolutional neural networks and applications: A survey
(
Academic Press
, 2021 , Article)
During the last decade, Convolutional Neural Networks (CNNs) have become the de facto standard for various Computer Vision and Machine Learning operations. CNNs are feed-forward Artificial Neural Networks (ANNs) with ...
Progressive Operational Perceptrons
(
Elsevier B.V.
, 2017 , Article)
There are well-known limitations and drawbacks on the performance and robustness of the feed-forward, fully-connected Artificial Neural Networks (ANNs), or the so-called Multi-Layer Perceptrons (MLPs). In this study we ...
Long-term epileptic EEG classification via 2D mapping and textural features
(
Elsevier Ltd
, 2015 , Article)
Interpretation of long-term Electroencephalography (EEG) records is a tiresome task for clinicians. This paper presents an efficient, low cost and novel approach for patient-specific classification of long-term epileptic ...
Multifrequency Polsar Image Classification Using Dual-Band 1D Convolutional Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
In this work, we propose a novel classification approach based on dual-band one-dimensional Convolutional Neural Networks (1D-CNNs) for classification of multifrequency polarimetric SAR (PolSAR) data. The proposed approach ...
Self-organized operational neural networks for severe image restoration problems
(
Elsevier Ltd
, 2021 , Article)
Discriminative learning based on convolutional neural networks (CNNs) aims to perform image restoration by learning from training examples of noisy-clean image pairs. It has become the go-to methodology for tackling image ...
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 ...