Browsing by Subject "Convolution"
Now showing items 1-20 of 37
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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 ... -
1D Convolutional Neural Networks Versus Automatic Classifiers for Known LPI Radar Signals under White Gaussian Noise
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)In this study we analyze the signal classification performances of various classifiers for deterministic signals under the additive White Gaussian Noise (WGN) in a wide range of signal to noise ratio (SNR) levels (-40dB ... -
A Deep Learning Model for LoRa Signals Classification Using Cyclostationay Features
( IEEE Computer Society , 2021 , Conference Paper)With the witnessed exponential growth of Internet of Things (IoT) nodes deployment following the emerging applications, multiple variants of technologies have been proposed to handle the IoT requirements. Among the proposed ... -
Actuator Fault Diagnosis in Multi-Zone HVAC Systems using 2D Convolutional Neural Networks
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)This paper presents a novel supervised on-line fault diagnosis strategy in Heating, Ventilation, and Air conditioning (HVAC) systems for actuator faults using 2D Convolutional Neural Networks. It is based on an efficient ... -
Application of data-driven attack detection framework for secure operation in smart buildings
( Elsevier Ltd , 2021 , Article)With the rapid advancement in the industrial control technologies and the increased deployment of the industrial Internet of Things (IoT) in the buildings sector, this work presents an analysis of the security of the ... -
Binarization of Degraded Document Images Using Convolutional Neural Networks and Wavelet-Based Multichannel Images
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Article)Convolutional neural networks (CNNs) have previously been broadly utilized to binarize document images. These methods have problems when faced with degraded historical documents. This paper proposes the utilization of CNNs ... -
Binarization of degraded document images using convolutional neural networks based on predicted two-channel images
( IEEE Computer Society , 2019 , Conference Paper)Due to the poor condition of most of historical documents, binarization is difficult to separate document image background pixels from foreground pixels. This paper proposes Convolutional Neural Networks (CNNs) based on ... -
Convolutional neural networks for real-time and wireless damage detection
( Springer New York LLC , 2020 , Conference Paper)Structural damage detection methods available for structural health monitoring applications are based on data preprocessing, feature extraction, and feature classification. The feature classification task requires considerable ... -
Convolutional Sparse Support Estimator Network (CSEN): From Energy-Efficient Support Estimation to Learning-Aided Compressive Sensing
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Support estimation (SE) of a sparse signal refers to finding the location indices of the nonzero elements in a sparse representation. Most of the traditional approaches dealing with SE problems are iterative algorithms ... -
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ... -
Deep Learning for Reliable Classification of COVID-19, MERS, and SARS from Chest X-ray Images
( Springer , 2022 , Article)Novel coronavirus disease (COVID-19) is an extremely contagious and quickly spreading coronavirus infestation. Severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), which outbreak in 2002 ... -
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Commercial unmanned aerial vehicles, or drones, are getting increasingly popular in the last few years. The fact that these drones are highly accessible to public may bring a range of security and technical issues to ... -
Early Bearing Fault Diagnosis of Rotating Machinery by 1D Self-Organized Operational Neural Networks
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Preventive maintenance of modern electric rotating machinery (RM) is critical for ensuring reliable operation, preventing unpredicted breakdowns and avoiding costly repairs. Recently many studies investigated machine ... -
Efficiency validation of one dimensional convolutional neural networks for structural damage detection using a SHM benchmark data
( International Institute of Acoustics and Vibration, IIAV , 2018 , Conference Paper)In this paper, a novel one dimensional convolution neural network (1D-CNN) based structural damage assessment technique is validated with a benchmark study published by IASC-ASCE Structural Health Monitoring Task Group in ... -
End-to-End Image Steganography Using Deep Convolutional Autoencoders
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Image steganography is used to hide a secret image inside a cover image in plain sight. Traditionally, the secret data is converted into binary bits and the cover image is manipulated statistically to embed the secret ... -
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. ... -
FSC-Set: Counting, Localization of Football Supporters Crowd in the Stadiums
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)Counting the number of people in a crowd has gained attention in the last decade. Due to its benefit to many applications such as crowd behavior analysis, crowd management, and video surveillance systems, etc. Counting ... -
Gait recognition for person re-identification
( Springer , 2021 , Article)Person re-identification across multiple cameras is an essential task in computer vision applications, particularly tracking the same person in different scenes. Gait recognition, which is the recognition based on the ... -
Handcrafted features with convolutional neural networks for detection of tumor cells in histology images
( IEEE Computer Society , 2016 , Conference Paper)Detection of tumor nuclei in cancer histology images requires sophisticated techniques due to the irregular shape, size and chromatin texture of the tumor nuclei. Some very recently proposed methods employ deep convolutional ... -
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 ...