Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Pius Kwao Gadosey"'
Autor:
Pius Kwao Gadosey, Yujian Li, Enock Adjei Agyekum, Ting Zhang, Zhaoying Liu, Peter T. Yamak, Firdaous Essaf
Publikováno v:
Diagnostics, Vol 10, Iss 2, p 110 (2020)
During image segmentation tasks in computer vision, achieving high accuracy performance while requiring fewer computations and faster inference is a big challenge. This is especially important in medical imaging tasks but one metric is usually compro
Externí odkaz:
https://doaj.org/article/2bad436064e142649627f412bc06829c
Publikováno v:
CNIOT
The examination of the lungs is an important part of the annual physical examination. There are hundreds or thousands of cases in the physical examination, and each case contains many lung cross-sectional CT images. These all require professional doc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7dfe466edb68982725b8f18f1f74600
https://doi.org/10.1145/3398329.3398337
https://doi.org/10.1145/3398329.3398337
Publikováno v:
ICCAI
As a research area of computer vision and deep learning, scene understanding has attracted a lot of attention in recent years. One major challenge encountered is obtaining high levels of segmentation accuracy while dealing with the computational cost
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca0812f29625d6dedd2416e7f9ba4361
https://doi.org/10.1145/3404555.3404629
https://doi.org/10.1145/3404555.3404629
Publikováno v:
ICCAI
In lung cancer computer-aided diagnosis (CAD), the correct segmentation of the lung parenchyma is particularly important. In order to reduce the detection area, save computational time and improve accuracy, lung tissue needs to be extracted in advanc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48ee1e18a130c9916d294e87e7061b28
https://doi.org/10.1145/3404555.3404647
https://doi.org/10.1145/3404555.3404647
Autor:
Ting Zhang, Yujian Li, Zhaoying Liu, Peter T. Yamak, Enock Adjei Agyekum, Firdaous Essaf, Pius Kwao Gadosey
Publikováno v:
Diagnostics
Volume 10
Issue 2
Diagnostics, Vol 10, Iss 2, p 110 (2020)
Volume 10
Issue 2
Diagnostics, Vol 10, Iss 2, p 110 (2020)
During image segmentation tasks in computer vision, achieving high accuracy performance while requiring fewer computations and faster inference is a big challenge. This is especially important in medical imaging tasks but one metric is usually compro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::988f71e8939c4ff39720edb4e5ce5b80
Publikováno v:
Intelligent Data Analysis. 22:309-323
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::725cad11f9fb997dedd356f5d40f95e6
https://doi.org/10.3233/ida-163337
https://doi.org/10.3233/ida-163337
Publikováno v:
Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence.
A critical area of machine learning is Time Series forecasting, as various forecasting problems contain a time component. A series of observations taken chronologically in time is known as a Time Series. In this research, however, we aim to compare t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::67bc92855ef668612bd5bd64b66779c7
https://doi.org/10.1145/3377713.3377722
https://doi.org/10.1145/3377713.3377722
Publikováno v:
AIIPCC
With the influx of several kinds of mobile electronic devices alongside the increasing popularity of deep learning networks in performing computer vision tasks, it is natural that demands for delivering them on smaller devices will increase. The auth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::492d149ad43b3765e92372be4dfe31f6
https://doi.org/10.1145/3371425.3371481
https://doi.org/10.1145/3371425.3371481
Publikováno v:
International Journal of Computational Science and Engineering. 21:522
Deep learning architectures which are exceptionally deep have exhibited to be incredibly powerful models for image processing. As the architectures become deep, it introduces challenges and difficulties in the training process such as overfitting, co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dd4d62efd3b3bfe26eeac38cc68fd27
https://doi.org/10.1504/ijcse.2020.106866
https://doi.org/10.1504/ijcse.2020.106866