Artificial intelligence, Feature extraction, Pattern recognition, Convolutional neural network and Artificial neural network are his primary areas of study. His studies in Artificial intelligence integrate themes in fields like Internal medicine and Computer vision. His Feature extraction research incorporates elements of Classifier, Random forest and Preprocessor.
His Pattern recognition research focuses on Sensitivity and how it relates to Phonocardiogram, Feedforward neural network, Linear discriminant analysis and Sequence. His work carried out in the field of Convolutional neural network brings together such families of science as Training set, Anomaly detection, Structural health monitoring, Fault detection and isolation and Benchmark database. Serkan Kiranyaz interconnects Particle swarm optimization and Swarm behaviour in the investigation of issues within Artificial neural network.
Serkan Kiranyaz focuses on Artificial intelligence, Pattern recognition, Feature extraction, Convolutional neural network and Artificial neural network. The various areas that Serkan Kiranyaz examines in his Artificial intelligence study include Machine learning and Computer vision. His Pattern recognition research integrates issues from Particle swarm optimization and Deep learning.
His study in Feature extraction is interdisciplinary in nature, drawing from both Feature detection, Image retrieval, Visual Word, Image texture and Principal component analysis. He has researched Convolutional neural network in several fields, including Training set, Anomaly detection, Structural health monitoring, Fault detection and isolation and Benchmark. His study in the field of Biological neuron model is also linked to topics like Operator.
His primary scientific interests are in Artificial intelligence, Convolutional neural network, Pattern recognition, Artificial neural network and Benchmark. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Machine learning. The concepts of his Convolutional neural network study are interwoven with issues in Identification, Anomaly detection, Training set and Fault detection and isolation.
In general Pattern recognition study, his work on Classifier often relates to the realm of Sliding window protocol, thereby connecting several areas of interest. His Artificial neural network research includes elements of Image restoration and Leverage. The study incorporates disciplines such as Real-time computing, Data pre-processing, Feature selection and Structural health monitoring in addition to Feature extraction.
Serkan Kiranyaz mostly deals with Artificial intelligence, Convolutional neural network, Pattern recognition, Machine learning and Perceptron. His biological study focuses on Deep learning. Serkan Kiranyaz combines subjects such as Identification, Artificial neural network, Anomaly detection, Fault detection and isolation and Feature extraction with his study of Convolutional neural network.
His research in Artificial neural network tackles topics such as Training set which are related to areas like Network complexity. His Feature extraction study incorporates themes from Cognitive neuroscience of visual object recognition, Biometrics, Facial recognition system, Face and Structural health monitoring. His work on Classifier as part of general Pattern recognition research is frequently linked to Sliding window protocol, bridging the gap between disciplines.
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Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks
Serkan Kiranyaz;Turker Ince;Moncef Gabbouj.
IEEE Transactions on Biomedical Engineering (2016)
Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks
Turker Ince;Serkan Kiranyaz;Levent Eren;Murat Askar.
IEEE Transactions on Industrial Electronics (2016)
A Generic and Robust System for Automated Patient-Specific Classification of ECG Signals
T. Ince;S. Kiranyaz;M. Gabbouj.
IEEE Transactions on Biomedical Engineering (2009)
Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks
Osama Abdeljaber;Onur Avci;Serkan Kiranyaz;Moncef Gabbouj.
Journal of Sound and Vibration (2017)
Evolutionary artificial neural networks by multi-dimensional particle swarm optimization
Serkan Kiranyaz;Turker Ince;Alper Yildirim;Moncef Gabbouj.
Neural Networks (2009)
1D convolutional neural networks and applications: A survey
Serkan Kiranyaz;Onur Avci;Osama Abdeljaber;Turker Ince.
Mechanical Systems and Signal Processing (2021)
A Generic Intelligent Bearing Fault Diagnosis System Using Compact Adaptive 1D CNN Classifier
Levent Eren;Turker Ince;Serkan Kiranyaz.
Journal of Signal Processing Systems (2019)
Integrating Color Features in Polarimetric SAR Image Classification
Stefan Uhlmann;Serkan Kiranyaz.
IEEE Transactions on Geoscience and Remote Sensing (2014)
Fractional Particle Swarm Optimization in Multidimensional Search Space
S. Kiranyaz;T. Ince;A. Yildirim;M. Gabbouj.
systems man and cybernetics (2010)
Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition
Serkan Kiranyaz;Turker Ince;Moncef Gabbouj.
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