Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Dhanesh Ramachandram"'
Autor:
Dhanesh Ramachandram, Jose Luis Ramirez-GarciaLuna, Robert D J Fraser, Mario Aurelio Martínez-Jiménez, Jesus E Arriaga-Caballero, Justin Allport
Publikováno v:
JMIR mHealth and uHealth, Vol 10, Iss 4, p e36977 (2022)
BackgroundComposition of tissue types within a wound is a useful indicator of its healing progression. Tissue composition is clinically used in wound healing tools (eg, Bates-Jensen Wound Assessment Tool) to assess risk and recommend treatment. Howev
Externí odkaz:
https://doaj.org/article/0509231ecd3449178b67536e5fa9951c
Autor:
Rishabh Gupta, Lucas Goldstone, Shira Eisen, Dhanesh Ramachandram, Amy Cassata, Robert D. J. Fraser, Jose L. Ramirez-GarciaLuna, Robert Bartlett, Justin Allport
Chronic wounds affect millions of people worldwide every year. An adequate assessment of a wound's prognosis is a critical aspect of wound care since it assists clinicians in understanding wound healing status, severity, triaging and determining the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21555e1535e4129cd40bfb36c0908933
https://doi.org/10.36227/techrxiv.21067261
https://doi.org/10.36227/techrxiv.21067261
Autor:
Dhanesh Ramachandram, Jose Luis Ramirez-GarciaLuna, Robert D J Fraser, Mario Aurelio Martínez-Jiménez, Jesus E Arriaga-Caballero, Justin Allport
BACKGROUND Composition of tissue types within a wound is a useful indicator of its healing progression. Tissue composition is clinically used in wound healing tools (eg, Bates-Jensen Wound Assessment Tool) to assess risk and recommend treatment. Howe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ea5917b0388bd3a07652c5b61e18df8
https://doi.org/10.2196/preprints.36977
https://doi.org/10.2196/preprints.36977
Publikováno v:
Neurocomputing. 298:80-89
A popular testbed for deep learning has been multimodal recognition of human activity or gesture involving diverse inputs like video, audio, skeletal pose and depth images. Deep learning architectures have excelled on such problems due to their abili
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c06590c6ea2e034099c68ec498993b5
https://doi.org/10.1016/j.neucom.2017.11.071
https://doi.org/10.1016/j.neucom.2017.11.071
Autor:
Dhanesh Ramachandram, Graham W. Taylor
Publikováno v:
IEEE Signal Processing Magazine. 34:96-108
The success of deep learning has been a catalyst to solving increasingly complex machine-learning problems, which often involve multiple data modalities. We review recent advances in deep multimodal learning and highlight the state-of the art, as wel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0a8ed13307612c1132d59492bf4ae3a
https://doi.org/10.1109/msp.2017.2738401
https://doi.org/10.1109/msp.2017.2738401
Autor:
Graham W. Taylor, Dhanesh Ramachandram
Publikováno v:
Journal of Computational Vision and Imaging Systems. 3
We present a image segmentation method based on deep hypercolumndescriptors which produces state-of-the-art results for thesegmentation of several classes of benign and malignant skin lesions.We achieve a Jaccard index of 0.792 on the 2017 ISIC SkinL
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::343531bba28b730532a68cb78620b0cf
https://doi.org/10.15353/vsnl.v3i1.173
https://doi.org/10.15353/vsnl.v3i1.173
Publikováno v:
International Journal of Computer and Communication Engineering. :444-448
In object class recognition, the state-of-the-art works shows using combination varies local features may produce a good performance in recognition. These local features may have a different performance on one category to other category which it depe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::692393eff55fa040c7dbc97390822ebf
https://doi.org/10.7763/ijcce.2012.v1.109
https://doi.org/10.7763/ijcce.2012.v1.109
Publikováno v:
Knowledge and Information Systems. 31:193-221
In recent years, the machine learning community has witnessed a tremendous growth in the development of kernel-based learning algorithms. However, the performance of this class of algorithms greatly depends on the choice of the kernel function. Kerne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a980ed8242fe371ab9bb0c82afa92bbd
https://doi.org/10.1007/s10115-011-0404-6
https://doi.org/10.1007/s10115-011-0404-6
Publikováno v:
Multimedia Tools and Applications. 61:69-86
In this paper we show how to resolve the ambiguity of concepts that are extracted from visual stream with the help of identified concepts from associated textual stream. The disambiguation is performed at the concept-level based on semantic closeness
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05e5212b036d9533175af58959e0f837
https://doi.org/10.1007/s11042-010-0707-8
https://doi.org/10.1007/s11042-010-0707-8
Publikováno v:
Artificial Intelligence Review. 34:291-308
This paper presents a comparative study of Bayesian belief network structure learning algorithms with a view to identify a suitable algorithm for modeling the contextual relations among objects typically found in natural imagery. Four popular structu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b88058340daf17852c65914e8245f3d4
https://doi.org/10.1007/s10462-010-9176-8
https://doi.org/10.1007/s10462-010-9176-8