Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Andrew P. Paplinski"'
Publikováno v:
Neurocomputing. 462:69-87
A common problem in pixelwise classification or semantic segmentation is class imbalance, which tends to reduce the classification accuracy of minority-class regions. An effective way to address this is to tune the loss function, particularly when Cr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c330cb4415b53e2a3ddd4cb815eca8e4
https://doi.org/10.1016/j.neucom.2021.07.055
https://doi.org/10.1016/j.neucom.2021.07.055
Publikováno v:
Internet of Things ISBN: 9783031055270
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c7eb75c2d2d1d6fea41dbdcefb23b85
https://doi.org/10.1007/978-3-031-05528-7_3
https://doi.org/10.1007/978-3-031-05528-7_3
Publikováno v:
Neurocomputing. 477:61
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5fe9d1d01ceaefba04c7bd5972599bc2
https://doi.org/10.1016/j.neucom.2022.01.009
https://doi.org/10.1016/j.neucom.2022.01.009
Publikováno v:
FMEC
Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (C
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b420f3cbbff81eda26b935a7127a2ed
https://doi.org/10.1109/fmec.2018.8364052
https://doi.org/10.1109/fmec.2018.8364052
Publikováno v:
Neural Information Processing ISBN: 9783030042387
ICONIP (7)
ICONIP (7)
The diagnosis and treatment of prostate cancer requires the accurate segmentation of the prostate in Magnetic Resonance Images (MRI). Manual segmentation is currently the most accurate method of performing this task. However, this requires specialist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3cf8d266aeebc0dd0b139d05480b0ed6
https://doi.org/10.1007/978-3-030-04239-4_46
https://doi.org/10.1007/978-3-030-04239-4_46
Publikováno v:
VCIP
Images typically have many levels of detail and the suitability of a segmentation depends on application requirements. Thus, it is imperative that the user/application be given the option to select the ‘optimal’ segmentation that captures the des
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8aaf09fe0d89433293b8687d90a938c8
https://doi.org/10.1109/vcip.2017.8305030
https://doi.org/10.1109/vcip.2017.8305030
Publikováno v:
Sustainable Cloud and Energy Services ISBN: 9783319622378
Virtual machine (VM) consolidation is one of the key mechanisms of designing an energy-efficient dynamic Cloud resource management system. It is based on the premise that migrating VMs into fewer number of Physical Machines (PMs) can achieve both opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a746ed1a6b2b3a6ea9ca5c31d0b6c17e
https://doi.org/10.1007/978-3-319-62238-5_6
https://doi.org/10.1007/978-3-319-62238-5_6
Autor:
Hayley M. Reynolds, Andrew P. Paplinski, John M. Betts, Mohammad Ali Jan Ghasab, Annette Haworth
Publikováno v:
ICIP
3D visualisation is being used increasingly to improve the accuracy of biopsies and seed placement for prostate cancer brachytherapy (the implantation of small radioactive ‘seeds’ for radiotherapy). The construction of a 3D model requires the seg
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0bbf06b5737a3f68c5e77185ba20ae9c
https://doi.org/10.1109/icip.2017.8297124
https://doi.org/10.1109/icip.2017.8297124
Publikováno v:
Neural Information Processing ISBN: 9783319700922
ICONIP (4)
ICONIP (4)
The scarcity of labeled data has limited the capacity of convolutional neural networks (CNNs) until not long ago and still represents a serious problem in a number of image processing applications. Unsupervised methods have been shown to perform well
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43accb266dcc355cf6a0e80cc63c284c
https://doi.org/10.1007/978-3-319-70093-9_49
https://doi.org/10.1007/978-3-319-70093-9_49
Publikováno v:
DICTA
This paper presents a hierarchical image segmentation algorithm based on the principle of mutual nearest neighbours. Image segmentation remains a great challenge in the computer vision community. To solve this problem, various algorithms have been pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::271fb803912783a7d3025751f59cc6fc
https://doi.org/10.1109/dicta.2016.7797047
https://doi.org/10.1109/dicta.2016.7797047