Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Hongmei Mi"'
Publikováno v:
Sensors, Vol 23, Iss 5, p 2676 (2023)
Anomalous road manhole covers pose a potential risk to road safety in cities. In the development of smart cities, computer vision techniques use deep learning to automatically detect anomalous manhole covers to avoid these risks. One important proble
Externí odkaz:
https://doaj.org/article/1466516890e54334b57211f13c2fa2fd
Publikováno v:
Neurocomputing. 456:147-155
Community detection has emerged during the last decade as one of the most challenging problems in network science, which has been revisited with network representation learning recently and has attracted considerable attention. Many approaches have b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fc9573ea4e21b508e50a121e4215e3c
https://doi.org/10.1016/j.neucom.2021.05.058
https://doi.org/10.1016/j.neucom.2021.05.058
Weakly-supervised learning for community detection based on graph convolution in attributed networks
Publikováno v:
International Journal of Machine Learning and Cybernetics. 12:3529-3539
Community detection in complex networks has been revisited with graph deep learning recently and has attracted great attention. It is often challenging to uncover underlying communities on attributed networks because of the complexity and diversity o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b59b451e4ea06b1f939d4f01572d1328
https://doi.org/10.1007/s13042-021-01400-x
https://doi.org/10.1007/s13042-021-01400-x
Autor:
Dongxu Yang, Hongya Lin, Binggang Xiao, Fenglei Guo, Mingyue Gu, Lihua Xiao, Limin Hu, Hongmei Mi
Publikováno v:
Optical and Quantum Electronics. 50
A tunable terahertz dual band absorber consisted of graphene ribbon arrays and a graphene sheet with near-unity absorption is proposed and studied in this letter. With the coupling enhancement of graphene ribbon and graphene sheet, a perfect dual ban
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03572c9e9dfb9a9e77269e9a9ba38396
https://doi.org/10.1007/s11082-018-1638-2
https://doi.org/10.1007/s11082-018-1638-2
Publikováno v:
Medical Image Analysis
Medical Image Analysis, Elsevier, 2015, 23 (1), pp.84-91
Medical Image Analysis, Elsevier, 2015, 23 (1), pp.84-91
Tumor response to treatment varies among patients. Patient-specific prediction of tumor evolution based on medical images during the treatment can help to build and adapt patient's treatment planning in a non-invasive way. Personalized tumor growth m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e1e60a4c6b08b23f7834bc0124f6158
https://doi.org/10.1016/j.media.2015.04.016
https://doi.org/10.1016/j.media.2015.04.016
Publikováno v:
Artificial Intelligence in Medicine
Artificial Intelligence in Medicine, Elsevier, 2015, 64 (3), pp.195-204. ⟨10.1016/j.artmed.2015.07.002⟩
Artificial Intelligence in Medicine, Elsevier, 2015, 64 (3), pp.195-204. ⟨10.1016/j.artmed.2015.07.002⟩
HighlightsA novel wrapper method searches forward in a hierarchical feature subset space.Prior domain knowledge is incorporated into the selection procedure.Promising results are obtained on two cancer-patient datasets. ObjectiveRecurrence of cancer
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7cecbfc118fffacd1bea4e3e321226e
https://pubmed.ncbi.nlm.nih.gov/26303106
https://pubmed.ncbi.nlm.nih.gov/26303106
Publikováno v:
Computational Methods for Molecular Imaging ISBN: 9783319184302
The recurrence of cancer increases the risk of death. The ability to predict such recurrence could be beneficial to planning treatment. We aim to find a predictive feature subset from a series of spatiotemporal PET image characteristics, including SU
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1df28d8edf68ef397c075fbd3154578
https://doi.org/10.1007/978-3-319-18431-9_11
https://doi.org/10.1007/978-3-319-18431-9_11
Autor:
Caroline Petitjean, H.C. Chen, Bernard Dubray, Pierre Vera, Cliff G. Robinson, Harold Li, Hongmei Mi, Su Ruan
Publikováno v:
In Annual Meeting of the American Society for Radiation Oncology
In Annual Meeting of the American Society for Radiation Oncology, 2015, San Antonio, United States
In Annual Meeting of the American Society for Radiation Oncology, 2015, San Antonio, United States
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::00294eee1a7eefe8519ee81d642a7e2f
https://hal.archives-ouvertes.fr/hal-01659549
https://hal.archives-ouvertes.fr/hal-01659549
Publikováno v:
IEEE Transactions on Medical Imaging
IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2014, 33 (4), pp.995-1003
IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2014, 33 (4), pp.995-1003
We propose a patient-specific model based on partial differential equation to predict the evolution of lung tumors during radiotherapy. The evolution of tumor cell density is formulated by three terms: 1) advection describing the advective flux trans
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c5f58e7d411a3ad7aea6740b6c98807
https://hal.archives-ouvertes.fr/hal-00945916
https://hal.archives-ouvertes.fr/hal-00945916
Publikováno v:
xx
IEEE International Symposium on Biomedical Imaging
IEEE International Symposium on Biomedical Imaging, Apr 2014, Beijing, China
ISBI
IEEE International Symposium on Biomedical Imaging
IEEE International Symposium on Biomedical Imaging, Apr 2014, Beijing, China
ISBI
The segmentation of tumor on PET images is an important step for treatment planning process during the radiotherapy. In this paper, we present an automatic segmentation method on PET images based on the random walks (RW) algorithm. We propose an exte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f447f3a09e5eac639357120758b64d1
https://hal.archives-ouvertes.fr/hal-00949806
https://hal.archives-ouvertes.fr/hal-00949806