Accurate detection of autism using Douglas-Peucker algorithm, sparse coding based feature map** and convolutional neural network techniques with EEG signals
Abstract Autism Spectrum Disorders (ASD) is a collection of complicated neurological
disorders that first show in early childhood. Electroencephalogram (EEG) signals are widely …
disorders that first show in early childhood. Electroencephalogram (EEG) signals are widely …
[PDF][PDF] Comparison of machine learning techniques for fetal heart rate classification
Cardiotocography is a monitoring technique providing important and vital information on
fetal status during antepartum and intrapartum periods. The advances in modern obstetric …
fetal status during antepartum and intrapartum periods. The advances in modern obstetric …
Comparison of extreme learning machine and deep learning model in the estimation of the fresh properties of hybrid fiber-reinforced SCC
This paper studied the estimation of fresh properties of hybrid fiber-reinforced self-
compacting concrete (HR-SCC) mixtures with different types and combinations of fibers by …
compacting concrete (HR-SCC) mixtures with different types and combinations of fibers by …
Prediction of compressive strength of nano-silica modified engineering cementitious composites exposed to high temperatures using hybrid deep learning models
H Tanyildizi - Expert Systems with Applications, 2024 - Elsevier
This study estimated the compressive strength of nano-silica-modified engineering
cementitious composites subjected to high temperatures using innovative hybrid deep …
cementitious composites subjected to high temperatures using innovative hybrid deep …
The investigation of multiresolution approaches for chest X-ray image based COVID-19 detection
COVID-19 is a novel virus, which has a fast spreading rate, and now it is seen all around the
world. The case and death numbers are increasing day by day. Some tests have been used …
world. The case and death numbers are increasing day by day. Some tests have been used …
Multi-category EEG signal classification develo** time-frequency texture features based Fisher Vector encoding method
Classification of electroencephalogram (EEG) signals plays an important role in the
diagnosis and treatment of brain diseases in the biomedical field. Here, we introduce a …
diagnosis and treatment of brain diseases in the biomedical field. Here, we introduce a …
Power quality event detection using a fast extreme learning machine
Monitoring Power Quality Events (PQE) is a crucial task for sustainable and resilient smart
grid. This paper proposes a fast and accurate algorithm for monitoring PQEs from a pattern …
grid. This paper proposes a fast and accurate algorithm for monitoring PQEs from a pattern …
Hybrid deep learning model for concrete incorporating microencapsulated phase change materials
The inclusion of microencapsulated phase change materials (MPCMs) in concrete promotes
thermal energy storage, thus enhancing sustainable design. Notwithstanding this …
thermal energy storage, thus enhancing sustainable design. Notwithstanding this …
Extreme learning machine for estimation of the engineering properties of self-compacting mortar with high-volume mineral admixtures
The utilization of supplementary cementitious materials obtained from industrial by-products
or wastes is one of the most effective ways to minimize the costs as well as environmental …
or wastes is one of the most effective ways to minimize the costs as well as environmental …
Predicting bond strength of corroded reinforcement by deep learning
H Tanyildizi - Computers and Concrete, 2022 - koreascience.kr
In this study, the extreme learning machine and deep learning models were devised to
estimate the bond strength of corroded reinforcement in concrete. The six inputs and one …
estimate the bond strength of corroded reinforcement in concrete. The six inputs and one …