Kurum Yazarı "Alçin, Ömer Faruk" Araştırma Çıktıları | TR-Dizin | WoS | Scopus | PubMed İçin Listeleme
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Accurate detection of autism using Douglas-Peucker algorithm, sparse coding based feature mapping and convolutional neural network techniques with EEG signals
Arı, Berna; Sobahi, Nebras; Alçin, Ömer Faruk; Sengur, Abdulkadir; Acharya, U.Rajendra (Elsevier B.V. All, 2022)Autism Spectrum Disorders (ASD) is a collection of complicated neurological disorders that first show in early childhood. Electroencephalogram (EEG) signals are widely used to record the electrical activities of the brain. ... -
Approach based on wavelet packet transform and 1D-RMLBP for drowsiness detection using EEG
Alçin, Ömer Faruk (Wiley-Blackwell, 2020)Early drowsiness detection may be crucial for the vehicle alertness system. Towards this, wearable technology, camera-based biophysical signals like electroencephalogram (EEG) approaches are utilised. In this Letter, the ... -
Classification of physical actions from surface EMG signals using the wavelet packet transform and local binary patterns
Alçin, Ömer Faruk; Budak, Ümit; Aslan, Muzaffer; Akbulut, Yaman; Cömert, Zafer; Akpınar, Muhammed H.; Şengür, Abdulkadir (Institute of Physics Publishing, 2020)Physical action recognition is a hot topic in human-machine interactions. It has potential uses in helping disabled people and in various robotic applications. Electromyography (EMG) signals measure the electrical activity ... -
Deep rhythm and long short term memory-based drowsiness detection
Türkoğlu, Muammer; Alçin, Ömer Faruk; Aslan, Muzaffer; Al-Zebari, Adel; Şengur, Abdülkadir (Elsevier, 2021)In this paper, a deep-rhythm-based approach is proposed for the efficient detection of drowsiness based on EEG recordings. In the proposed approach, EEG images are used instead of signals where the time and frequency ... -
Electrocardiogram beat classification using deep convolutional neural network techniques
Cömert, Zafer; Akbulut, Yaman; Akpınar, Muhammed H.; Alçin, Ömer Faruk; Budak, Ümit; Aslan, Muzaffer; Şengür, Abdulkadir (Institute of Physics Publishing, 2020)The electrocardiogram (ECG) is a useful method which enables the monitoring of various cardiac conditions, such as arrhythmia and heart rate variability (HRV). ECG beats help to determine various heart failures such as ... -
A New Framework for Automatic Detection of Patients With Mild Cognitive Impairment Using Resting-State EEG Signals
Siuly, Siuly; Alçin, Ömer Faruk; Kabir, Enamul; Şengür, Abdulkadir; Wang, Hua; Zhang, Yanchun; Whittaker, Frank (IEEE (Institute of Electrical and Electronics Engineers), 2020)Mild cognitive impairment (MCI) can be an indicator representing the early stage of Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major public health problem worldwide. Efficient detection ... -
A New Signal to Image Mapping Procedure and Convolutional Neural Networks for Efficient Schizophrenia Detection in EEG Recordings
Sobahi, Nebras; Çakar, Hakan; Arı, Berna; Alçin, Ömer Faruk; Şengür, Abdulkadir (Institute of Electrical and Electronics Engineers Inc., 2022)Machine learning has been densely used in most computer-aided medical diagnosis systems. These systems not only supported the physician’s decision but also accelerate the necessitated procedures. Electroencephalography ... -
Radiomics and deep learning approach to the differential diagnosis of parotid gland tumors
Gündüz, Emrah; Alçin, Ömer Faruk; Kızılay, Ahmet; Piazza, Cesare (Wolters Kluwer Health, 2022)All studies aimed at the differential diagnosis of benign vs. malignant PGTs or the identification of the commonest PGT subtypes were identified, and five studies were found that focused on deep learning-based differential ... -
Two-stepped majority voting for efficient EEG-based emotion classification
Ismael, Aras Masood; Alçin, Ömer Faruk; Abdalla, Karmand Hussein; Şengür, Abdulkadir (Springer, 2020)In this paper, a novel approach that is based on two-stepped majority voting is proposed for efficient EEG-based emotion classification. Emotion recognition is important for human-machine interactions. Facial features- and ...