Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Taegkeun Whangbo"'
Publikováno v:
Brain and Behavior, Vol 14, Iss 8, Pp n/a-n/a (2024)
Abstract Background Neurological disorders pose a significant health challenge, and their early detection is critical for effective treatment planning and prognosis. Traditional classification of neural disorders based on causes, symptoms, developmen
Externí odkaz:
https://doaj.org/article/4e7385e4ace240ee8e7b2f3edefc197d
Publikováno v:
IEEE Access, Vol 12, Pp 49762-49771 (2024)
The early detection and precise diagnosis of gastrointestinal diseases, particularly gastric cancer, play a vital role in improving patient survival rates and treatment outcomes. However, diagnosing these conditions can be challenging when symptoms a
Externí odkaz:
https://doaj.org/article/b6156dfeffed45fc82fa889e125be6c7
Publikováno v:
IEEE Access, Vol 11, Pp 87166-87177 (2023)
Gastric cancer is a leading cause of mortality, resulting in approximately 770000 deaths in the year 2020. Early detection theatres a vital role in facilitating targeted treatments for gastric conditions. One commonly employed method for diagnosis an
Externí odkaz:
https://doaj.org/article/2a9b3a91a41b473397de1c05cbc84fa6
Autor:
Ahmad Naeem, Tayyaba Anees, Khawaja Tehseen Ahmed, Rizwan Ali Naqvi, Shabir Ahmad, Taegkeun Whangbo
Publikováno v:
Complex & Intelligent Systems, Vol 9, Iss 2, Pp 1729-1751 (2022)
Abstract Deep learning for image retrieval has been used in this era, but image retrieval with the highest accuracy is the biggest challenge, which still lacks auto-correlation for feature extraction and description. In this paper, a novel deep learn
Externí odkaz:
https://doaj.org/article/e766a88ce160477587a15f52f49f1536
Publikováno v:
Heliyon, Vol 9, Iss 8, Pp e18783- (2023)
Wearable Sensors (WSs) are widely used in healthcare applications to monitor patient health. During the data transmission, dissemination requires additional time to transmit the details with minimum computation difficulties. The existing techniques c
Externí odkaz:
https://doaj.org/article/149fe50013014c1982f9aedc7a58dff6
Publikováno v:
Bioengineering, Vol 10, Iss 11, p 1332 (2023)
In the advancement of medical image super-resolution (SR), the Deep Residual Feature Distillation Channel Attention Network (DRFDCAN) marks a significant step forward. This work presents DRFDCAN, a model that innovates traditional SR approaches by in
Externí odkaz:
https://doaj.org/article/92673739baa041e1aba31460087fa468
Publikováno v:
Sensors, Vol 21, Iss 24, p 8355 (2021)
In wireless sensor networks (WSN), flooding increases the reliability in terms of successful transmission of a packet with higher overhead. The flooding consumes the resources of the network quickly, especially in sensor networks, mobile ad-hoc netwo
Externí odkaz:
https://doaj.org/article/62f80f6621f1441eb70f716ea69d6795
Efficient Classification of Motor Imagery Electroencephalography Signals Using Deep Learning Methods
Autor:
Ikhtiyor Majidov, Taegkeun Whangbo
Publikováno v:
Sensors, Vol 19, Iss 7, p 1736 (2019)
Single-trial motor imagery classification is a crucial aspect of brain–computer applications. Therefore, it is necessary to extract and discriminate signal features involving motor imagery movements. Riemannian geometry-based feature extraction met
Externí odkaz:
https://doaj.org/article/69b0ec0abb59408eaa68ee3a98648f18
Autor:
Khan, Habib Ullah, Abbas, Muhammad, Khan, Faheem, Nazir, Shah, Binbusayyis, Adel, Alabdultif, Abdulatif, Taegkeun, Whangbo
Publikováno v:
In Computers in Human Behavior August 2024 157
Publikováno v:
Journal of Digital Art Engineering and Multimedia. 10:81-91
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2a706b1c2481f64d3d751042df38d1f2
https://doi.org/10.29056/jdaem.2023.03.08
https://doi.org/10.29056/jdaem.2023.03.08