Zobrazeno 1 - 10
of 72
pro vyhledávání: '"Muhammet Fatih ASLAN"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Biotic stress imposed by pathogens, including fungal, bacterial, and viral, can cause heavy damage leading to yield reduction in maize. Therefore, the identification of resistant genes paves the way to the development of disease-resistant cu
Externí odkaz:
https://doaj.org/article/6dacd9bb148e4c908e2d8abb1efc5fa3
Autor:
Khairunnisa Hasikin, Khin Wee Lai, Suresh Chandra Satapathy, Kadir Sabanci, Muhammet Fatih Aslan
Publikováno v:
Frontiers in Digital Health, Vol 5 (2023)
Externí odkaz:
https://doaj.org/article/27d2865198974e869d33536a1893e8d1
Autor:
Mohamed Zul Fadhli Khairuddin, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Khin Wee Lai, Mohd Zamri Osman, Muhammet Fatih Aslan, Kadir Sabanci, Muhammad Mokhzaini Azizan, Suresh Chandra Satapathy, Xiang Wu
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
Workplace accidents can cause a catastrophic loss to the company including human injuries and fatalities. Occupational injury reports may provide a detailed description of how the incidents occurred. Thus, the narrative is a useful information to ext
Externí odkaz:
https://doaj.org/article/fd94a9713e66468d89a8ee0beb6244b6
Publikováno v:
IEEE Access, Vol 9, Pp 10054-10069 (2021)
Deep learning (DL) based localization and Simultaneous Localization and Mapping (SLAM) has recently gained considerable attention demonstrating remarkable results. Instead of constructing hand-crafted algorithms through geometric theories, DL based s
Externí odkaz:
https://doaj.org/article/d21db618820245c8b6426fb94e2495e4
Autor:
Muhammet Fatih Aslan, Khairunnisa Hasikin, Abdullah Yusefi, Akif Durdu, Kadir Sabanci, Muhammad Mokhzaini Azizan
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
Artificial intelligence researchers conducted different studies to reduce the spread of COVID-19. Unlike other studies, this paper isn't for early infection diagnosis, but for preventing the transmission of COVID-19 in social environments. Among the
Externí odkaz:
https://doaj.org/article/202614c48edb45689de54cefaf8836db
A Novel Proposal for Deep Learning-Based Diabetes Prediction: Converting Clinical Data to Image Data
Autor:
Muhammet Fatih Aslan, Kadir Sabanci
Publikováno v:
Diagnostics, Vol 13, Iss 4, p 796 (2023)
Diabetes, one of the most common diseases worldwide, has become an increasingly global threat to humans in recent years. However, early detection of diabetes greatly inhibits the progression of the disease. This study proposes a new method based on d
Externí odkaz:
https://doaj.org/article/121d90f55b264fe39de0d81c5a18ea83
Publikováno v:
Applied Sciences, Vol 13, Iss 1, p 206 (2022)
The objective of this study was to reveal the usefulness of image processing and machine learning for the non-destructive evaluation of the changes in mint leaves caused by two natural drying techniques. The effects of shade drying and open-air sun d
Externí odkaz:
https://doaj.org/article/983b9dc6660e43d493741e19338ee02b
Publikováno v:
Diagnostics, Vol 12, Iss 12, p 2926 (2022)
Among the leading causes of mortality and morbidity in people are lung and colon cancers. They may develop concurrently in organs and negatively impact human life. If cancer is not diagnosed in its early stages, there is a great likelihood that it wi
Externí odkaz:
https://doaj.org/article/d44951e004d841568abad658a9d49d98
Autor:
Ewa Ropelewska, Vanya Slavova, Kadir Sabanci, Muhammet Fatih Aslan, Veselina Masheva, Mariana Petkova
Publikováno v:
Agriculture, Vol 12, Iss 11, p 1887 (2022)
Artificial-intelligence-based analysis methods can provide objective and accurate results. This study aimed to evaluate the performance of machine learning algorithms to classify yeast-inoculated and uninoculated tomato samples using fluorescent spec
Externí odkaz:
https://doaj.org/article/88c61968b7df455faa0fcd466c7c82b3
Publikováno v:
Agriculture, Vol 12, Iss 10, p 1652 (2022)
The objective of this study was to evaluate differences between the red onion cultivar and breeding line using models based on selected fluorescence spectroscopic data built using machine-learning algorithms from different groups of Trees, Functions,
Externí odkaz:
https://doaj.org/article/5ca480b95a9c49d69b8e8806ed5286b5