Zobrazeno 1 - 3
of 3
pro vyhledávání: '"N. S. Francis"'
Publikováno v:
2020 IEEE 6th International Conference on Control Science and Systems Engineering (ICCSSE).
In this research, a Gated-SCNN is modelled with the Region Proposal Network (RPN) to identify cancerous CT lung images. The model is based on the principle of passing CT image scans via a double gateway. By doing so, the bronchopulmonary lung segment
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eaa9f35482040d3a9f47a506f9fb37ee
https://doi.org/10.1109/iccsse50399.2020.9171947
https://doi.org/10.1109/iccsse50399.2020.9171947
Publikováno v:
Journal of Physics: Conference Series. 1611:012062
The research deals with the development of an algorithm for detecting pathological formation in cystic fibrosis using the PSPNet model with focal loss. The model allows data sets to be entered in accordance to their similarities based on their pathol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d09928c7af8a1e6f473548a4d5d2699
https://doi.org/10.1088/1742-6596/1611/1/012062
https://doi.org/10.1088/1742-6596/1611/1/012062
Applying Ternary Net Weights to the R-Mask Neural Network to Identify Bronchopulmonary Lung Segments
Publikováno v:
Journal of Physics: Conference Series. 1611:012061
The purpose of this research is to develop an algorithm for detecting bronchopulmonary segments in lung Computer Tomography (CT) images, while reducing computational costs. The algorithm is implemented without the use of a graphics processor (GPU). T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc46f22aae4934b4e8d9a10e3128825e
https://doi.org/10.1088/1742-6596/1611/1/012061
https://doi.org/10.1088/1742-6596/1611/1/012061