Browsing by Subject "Convolution"
Now showing items 21-39 of 39
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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 ... -
Hybrid attack detection framework for industrial control systems using 1D-convolutional neural network and isolation forest
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Paper)Industrial control systems (ICSs) are used in various infrastructures and industrial plants for realizing their control operation and ensuring their safety. Concerns about the cybersecurity of industrial control systems ... -
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 ... -
Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
( Institute of Electrical and Electronics Engineers Inc. , 2016 , Article)Detection and classification of cell nuclei in histopathology images of cancerous tissue stained with the standard hematoxylin and eosin stain is a challenging task due to cellular heterogeneity. Deep learning approaches ... -
Mhad: Multi-human action dataset
( Springer , 2020 , Conference Paper)This paper presents a framework for a multi-action recognition method. In this framework, we introduce a new approach to detect and recognize the action of several persons within one scene. Also, considering the scarcity ... -
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 ... -
Novel Actuator Fault Diagnosis Framework for Multizone HVAC Systems Using 2-D Convolutional Neural Networks
( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)Heating, ventilation, and air conditioning (HVAC) systems are used to condition the indoor environment in buildings. They can be subjected to malfunctioning since they are the most extensively operated buildings' components ... -
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 ... -
Operational neural networks
( Springer , 2020 , Article)Feed-forward, fully connected artificial neural networks or the so-called multi-layer perceptrons are well-known universal approximators. However, their learning performance varies significantly depending on the function ... -
Pose-invariant face recognition with multitask cascade networks
( Springer Science and Business Media Deutschland GmbH , 2022 , Article)In this work, a face recognition method is proposed for face under pose variations using a multitask convolutional neural network (CNN). Furthermore, a pose estimation method followed by a face identification module is ... -
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 ... -
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
( Institute of Electrical and Electronics Engineers Inc. , 2016 , Article)Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ... -
Real-time phonocardiogram anomaly detection by adaptive 1D Convolutional Neural Networks
( Elsevier B.V. , 2020 , Article)The heart sound signals (Phonocardiogram ? PCG) enable the earliest monitoring to detect a potential cardiovascular pathology and have recently become a crucial tool as a diagnostic test in outpatient monitoring to assess ... -
Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network
( IEEE Computer Society , 2022 , Article)Objective: Noise and low quality of ECG signals acquired from Holter or wearable devices deteriorate the accuracy and robustness of R-peak detection algorithms. This paper presents a generic and robust system for R-peak ... -
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 ... -
Self-organized Operational Neural Networks with Generative Neurons
( Elsevier Ltd , 2021 , Article)Operational Neural Networks (ONNs) have recently been proposed to address the well-known limitations and drawbacks of conventional Convolutional Neural Networks (CNNs) such as network homogeneity with the sole linear neuron ... -
Short-term probabilistic building load forecasting based on feature integrated artificial intelligent approach
( Elsevier Ltd , 2022 , Article)Due to various influential factors that lead to instability and volatility of the building load, short-term building load forecasting is a gruelling task. This paper proposes a hybrid short-term building load probability ... -
Structural damage detection in real time: Implementation of 1D convolutional neural networks for SHM applications
( Springer , 2017 , Conference Paper)Most of the classical structural damage detection systems involve two processes, feature extraction and feature classification. Usually, the feature extraction process requires large computational effort which prevent the ...