Zobrazeno 1 - 10 of 23 pro vyhledávání: '"Fatma LATİFOĞLU"'
1
Akademický článek
A New Hybrid Approach Based on Time Frequency Images and Deep Learning Methods for Diagnosis of Migraine Disease and Investigation of Stimulus Effect
Autor: Fırat Orhanbulucu, Fatma Latifoğlu, Recep Baydemir
Publikováno v: Diagnostics, Vol 13, Iss 11, p 1887 (2023)
Migraine is a neurological disorder that is associated with severe headaches and seriously affects the lives of patients. Diagnosing Migraine Disease (MD) can be laborious and time-consuming for specialists. For this reason, systems that can assist s
Externí odkaz: https://doaj.org/article/1f11983f9c5a44ad9733b759ffab27f3
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2
Akademický článek
Distinguishing Parkinson’s Disease with GLCM Features from the Hankelization of EEG Signals
Autor: Mehmet Fatih Karakaş, Fatma Latifoğlu
Publikováno v: Diagnostics, Vol 13, Iss 10, p 1769 (2023)
This study proposes a novel method that uses electroencephalography (EEG) signals to classify Parkinson’s Disease (PD) and demographically matched healthy control groups. The method utilizes the reduced beta activity and amplitude decrease in EEG s
Externí odkaz: https://doaj.org/article/590987cd024441959e0bac66b7323917
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3
Akademický článek
Quantitative Electroencephalography Analysis for Improved Assessment of Consciousness Levels in Deep Coma Patients Using a Proposed Stimulus Stage
Autor: Çiğdem Gülüzar Altıntop, Fatma Latifoğlu, Aynur Karayol Akın, Ayşe Ülgey
Publikováno v: Diagnostics, Vol 13, Iss 8, p 1383 (2023)
“Coma” is defined as an inability to obey commands, to speak, or to open the eyes. So, a coma is a state of unarousable unconsciousness. In a clinical setting, the ability to respond to a command is often used to infer consciousness. Evaluation o
Externí odkaz: https://doaj.org/article/c3c253c69b5e45d2938d79e1fabfb0f4
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4
Classification Mental Workload Levels from EEG Signals with 1D Convolutional Neural Network
Autor: Recep Baydemir, Fatma Latifoğlu, Fırat Orhanbulucu
Publikováno v: The European Journal of Research and Development. 2:13-23
Mental workload (MWL) can be estimated according to the state of cognitive capacity after an activity. In this study, it is aimed to classify MWL levels from Electroencephalogram (EEG) signals recorded from a task moment. Using the proposed one-dimen
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ae1e250cc9f32a1e99b1902405ddf84b
https://doi.org/10.56038/ejrnd.v2i4.193
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6
Detection of ADHD from EEG signals using new hybrid decomposition and deep learning techniques
Autor: Mustafa Yasin Esas, Fatma Latifoğlu
Publikováno v: Journal of Neural Engineering.
Objective: Attention Deficit Hyperactivity Disorder (ADHD) is considered one of the most common psychiatric disorders in childhood. The incidence of this disease in the community draws an increasing graph from the past to the present. While the ADHD
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::061c327672ccb5f8d6603c098171206e
https://doi.org/10.1088/1741-2552/acc902
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7
Detection of amyotrophic lateral sclerosis disease by variational mode decomposition and convolution neural network methods from event-related potential signals
Autor: Fırat Orhanbulucu, Fatma Latifoğlu, Ramis Ileri
Publikováno v: TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES. 29:2840-2854
Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is a neurological disease that occurs as a result of damage to the nerves in the brain and restriction of muscle movements. Electroencephalography (EEG) is the most common metho
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47492f9d78ef4e3e04af35e61544e3cd
https://doi.org/10.3906/elk-2105-86
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8
A novel approach for detection of dyslexia using convolutional neural network with EOG signals
Autor: Ramis Ileri, Fatma Latifoğlu, Esra Demirci
© 2022, International Federation for Medical and Biological Engineering.Dyslexia is a learning disability in acquiring reading skills, even though the individual has the appropriate learning opportunity, adequate education, and appropriate sociocult
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5f25f8ca7dcb23bd7cddaa52e5fc071
https://avesis.kayseri.edu.tr/publication/details/d193e919-a412-491c-9d6b-f60a69ec2d7f/oai
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9
Beyond the colors: enhanced deep learning on invasive ductal carcinoma
Autor: Mustafa Ozturk, Munevver Baran, Fatma Latifoğlu
© 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.Breast cancer is one of the most common cancer-related causes of morbidity and mortality in women around the world, and its early detection is ess
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a78b73c8eae1167b5fd520aca9a0ea8
https://avesis.kayseri.edu.tr/publication/details/e7f11406-a51b-4d0c-a0b3-3469f695d0a5/oai
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10
Çok Amaçlı Atomik Yörünge Arama Algoritması ile Metasezgisel FIR Filtre Tasarımı
Autor: Mehmet Fatih KARAKAŞ, Fatma LATİFOĞLU
Publikováno v: European Journal of Science and Technology.
In this study, atomic orbital search, one of the newly proposed metaheuristic algorithms, is used to design high-performance and low-order FIR filters in MATLAB. The performance parameters of the designed filter were compared with the given literatur
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0732df0be018bebbffc73ee91f2bdd26
https://doi.org/10.31590/ejosat.1145842
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