Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Rahul Duggal"'
Publikováno v:
PLoS ONE, Vol 13, Iss 12, p e0207908 (2018)
Plasma cell segmentation is the first stage of a computer assisted automated diagnostic tool for multiple myeloma (MM). Owing to large variability in biological cell types, a method for one cell type cannot be applied directly on the other cell types
Externí odkaz:
https://doaj.org/article/3b528f7a92ff4874a08a0fcfb51b3711
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3f54ebb354ef6508a6776898f25cb7c
https://doi.org/10.1109/bigdata52589.2021.9671980
https://doi.org/10.1109/bigdata52589.2021.9671980
Publikováno v:
2021 IEEE International Conference on Big Data (Big Data).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b4eb708bb820a3054d60294408b9fe59
https://doi.org/10.1109/bigdata52589.2021.9671807
https://doi.org/10.1109/bigdata52589.2021.9671807
Autor:
Omar Shaikh, Fred Hohman, Duen Horng Chau, Austin P. Wright, Rahul Duggal, Nilaksh Das, Haekyu Park
Publikováno v:
IEEE transactions on visualization and computer graphics. 28(1)
Existing research on making sense of deep neural networks often focuses on neuron-level interpretation, which may not adequately capture the bigger picture of how concepts are collectively encoded by multiple neurons. We present NeuroCartography, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1aa1378d6d259b26f84cb56dfbba8285
https://pubmed.ncbi.nlm.nih.gov/34587079
https://pubmed.ncbi.nlm.nih.gov/34587079
Publikováno v:
CVPR
We tackle the problem of visual search under resource constraints. Existing systems use the same embedding model to compute representations (embeddings) for the query and gallery images. Such systems inherently face a hard accuracy-efficiency trade-o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b6ca5009155a60a032f7302fc3aa1db
Publikováno v:
WWW
In recent years, significant attention has been devoted towards integrating deep learning technologies in the healthcare domain. However, to safely and practically deploy deep learning models for home health monitoring, two significant challenges mus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::622603025d2a3bb46b78e7d078048b70
http://arxiv.org/abs/2001.11363
http://arxiv.org/abs/2001.11363
Autor:
Anvit Mangal, Shiv Gehlot, Anubha Gupta, Rahul Duggal, Nisarg Thakkar, Lalit Kumar, Devprakash Satpathy, Ritu Gupta
Publikováno v:
Medical Image Analysis. 65:101788
Stain normalization of microscopic images is the first pre-processing step in any computer-assisted automated diagnostic tool. This paper proposes Geometry-inspired Chemical-invariant and Tissue Invariant Stain Normalization method, namely GCTI-SN, f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44c94249f1ea209e1300ce2d4f1e638a
https://doi.org/10.1016/j.media.2020.101788
https://doi.org/10.1016/j.media.2020.101788
Publikováno v:
PLoS ONE, Vol 13, Iss 12, p e0207908 (2018)
PLoS ONE
PLoS ONE
Plasma cell segmentation is the first stage of a computer assisted automated diagnostic tool for multiple myeloma (MM). Owing to large variability in biological cell types, a method for one cell type cannot be applied directly on the other cell types
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24ca7a309b06ee45cb0c730eb1cc5320
https://doaj.org/article/3b528f7a92ff4874a08a0fcfb51b3711
https://doaj.org/article/3b528f7a92ff4874a08a0fcfb51b3711
Autor:
Anubha Gupta, Rahul Duggal
Publikováno v:
ICCV Workshops
This paper proposes a new activation function, namely, Parametric Tan Hyperbolic Linear Unit (P-TELU) for deep neural networks. The work is inspired from two recently proposed functions: Parametric RELU (P-RELU) and Exponential Linear Unit (ELU). The
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57e23c85ec3448de8348bd473cf58174
https://doi.org/10.1109/iccvw.2017.119
https://doi.org/10.1109/iccvw.2017.119
Publikováno v:
Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 ISBN: 9783319661780
MICCAI (3)
MICCAI (3)
Convolutional Neural Networks (CNNs) are typically trained in the RGB color space. However, in medical imaging, we believe that pixel stain quantities offer a fundamental view of the interaction between tissues and stain chemicals. Since the optical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60c1cc0b5ca6c4ba7f4bd61815ef8c58
https://doi.org/10.1007/978-3-319-66179-7_50
https://doi.org/10.1007/978-3-319-66179-7_50