Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Abdulkadir Sengu"'
Autor:
Muhammed Halil Akpinar, Abdulkadir Sengur, Massimo Salvi, Silvia Seoni, Oliver Faust, Hasan Mir, Filippo Molinari, U. Rajendra Acharya
Publikováno v:
IEEE Open Journal of Engineering in Medicine and Biology, Vol 6, Pp 183-192 (2025)
Generative Adversarial Networks (GANs) have emerged as a powerful tool in artificial intelligence, particularly for unsupervised learning. This systematic review analyzes GAN applications in healthcare, focusing on image and signal-based studies acro
Externí odkaz:
https://doaj.org/article/08ddb280e7c04d0da76ecae3552648f9
Autor:
Salih Taha Alperen Özçelik, Hüseyin Üzen, Abdulkadir Şengür, Hüseyin Fırat, Muammer Türkoğlu, Adalet Çelebi, Sema Gül, Nebras M. Sobahi
Publikováno v:
Diagnostics, Vol 14, Iss 23, p 2719 (2024)
Background: Dental disorders are one of the most important health problems, affecting billions of people all over the world. Early diagnosis is important for effective treatment planning. Precise dental disease segmentation requires reliable tooth nu
Externí odkaz:
https://doaj.org/article/20cad18bcb9f4758a83cb6978866e3e4
Autor:
Ahmed Ihsan Simsek, Erdinç Koç, Beste Desticioglu Tasdemir, Ahmet Aksöz, Muammer Turkoglu, Abdulkadir Sengur
Publikováno v:
Applied Sciences, Vol 14, Iss 23, p 10974 (2024)
The increasing demand for electric vehicles (EVs) requires accurate forecasting to support strategic decisions by manufacturers, policymakers, investors, and infrastructure developers. As EV adoption accelerates due to environmental concerns and tech
Externí odkaz:
https://doaj.org/article/641eae5ea90c410c8e54817e54368470
Autor:
Andac Imak, Adalet Celebi, Kamran Siddique, Muammer Turkoglu, Abdulkadir Sengur, Iftekhar Salam
Publikováno v:
IEEE Access, Vol 10, Pp 18320-18329 (2022)
Panoramic and periapical radiograph tools help dentists in diagnosing the most common dental diseases, such as dental caries. Generally, dental caries is manually diagnosed by dentists based on panoramic and periapical images. For several reasons, su
Externí odkaz:
https://doaj.org/article/4ccc5a6dbfbf43fd9d6a82d580e09223
Autor:
Berna Ari, Kamran Siddique, Omer Faruk Alcin, Muzaffer Aslan, Abdulkadir Sengur, Raja Majid Mehmood
Publikováno v:
IEEE Access, Vol 10, Pp 72171-72181 (2022)
Emotion perception is critical for behavior prediction. There are many ways to capture emotional states by observing the body and copying actions. Physiological markers such as electroencephalography (EEG) have gained popularity, as facial emotions m
Externí odkaz:
https://doaj.org/article/b016c90708494848b07a3983dd903293
Publikováno v:
IEEE Access, Vol 9, Pp 149456-149464 (2021)
In this paper, a novel approach was developed for Parkinson’s disease (PD) diagnosis based on speech disorders. When the literature about the speech disorders-based PD diagnosis was reviewed, it was seen that the most of approaches were concentrate
Externí odkaz:
https://doaj.org/article/480129834d834f12bb790643444cb80e
Publikováno v:
Brain Informatics, Vol 7, Iss 1, Pp 1-12 (2020)
Abstract 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 body gestures-ba
Externí odkaz:
https://doaj.org/article/cc7752225e2f4b3faeab56293dddbc23
Publikováno v:
IEEE Access, Vol 8, Pp 105376-105383 (2020)
The recognition of various lung sounds recorded using electronic stethoscopes plays a significant role in the early diagnoses of respiratory diseases. To increase the accuracy of specialist evaluations, machine learning techniques have been intensely
Externí odkaz:
https://doaj.org/article/3ca085bc56214955938a42d651732cf5
Publikováno v:
IEEE Access, Vol 8, Pp 66529-66537 (2020)
Cognitive prediction in the complicated and active environments is of great importance role in artificial learning. Classification accuracy of sound events has a robust relation with the feature extraction. In this paper, deep features are used in th
Externí odkaz:
https://doaj.org/article/fca0fd7324c64591b15e7782529c2101
Autor:
Hakan Uyanık, Salih Taha A. Ozcelik, Zeynep Bala Duranay, Abdulkadir Sengur, U. Rajendra Acharya
Publikováno v:
Diagnostics, Vol 12, Iss 10, p 2508 (2022)
Emotion recognition is one of the most important issues in human–computer interaction (HCI), neuroscience, and psychology fields. It is generally accepted that emotion recognition with neural data such as electroencephalography (EEG) signals, funct
Externí odkaz:
https://doaj.org/article/c5985f9570ae4b429f0b082e5b2d9f2b