Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Qicheng Lao"'
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. 33:4466-4478
Learning in nonstationary environments is one of the biggest challenges in machine learning. Nonstationarity can be caused by either task drift, i.e., the drift in the conditional distribution of labels given the input data, or the domain drift, i.e.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37fccea919798a5056bacebe6f519d24
https://doi.org/10.1109/tnnls.2021.3057453
https://doi.org/10.1109/tnnls.2021.3057453
Publikováno v:
Diabetic Foot Ulcers Grand Challenge ISBN: 9783031263538
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5ea55b8f118a666887d30721b4ff4f7
https://doi.org/10.1007/978-3-031-26354-5_3
https://doi.org/10.1007/978-3-031-26354-5_3
Autor:
Zekun Jiang, Jin Yin, Peilun Han, Nan Chen, Qingbo Kang, Yue Qiu, Yiyue Li, Qicheng Lao, Miao Sun, Dan Yang, Shan Huang, Jiajun Qiu, Kang Li
Publikováno v:
Quantitative imaging in medicine and surgery. 12(10)
This study set out to develop a computed tomography (CT)-based wavelet transforming radiomics approach for grading pulmonary lesions caused by COVID-19 and to validate it using real-world data.This retrospective study analyzed 111 patients with 187 p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d1c44894ad2478bef10062d4f83f293
https://pubmed.ncbi.nlm.nih.gov/36185061
https://pubmed.ncbi.nlm.nih.gov/36185061
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164484
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4e92e144e6d18af9642d9851116cf6b
https://doi.org/10.1007/978-3-031-16449-1_63
https://doi.org/10.1007/978-3-031-16449-1_63
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164330
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b3d6d544f2d71fcac199269a13a52fc
https://doi.org/10.1007/978-3-031-16434-7_6
https://doi.org/10.1007/978-3-031-16434-7_6
Publikováno v:
Medical image analysis. 79
Thyroid nodule segmentation and classification in ultrasound images are two essential but challenging tasks for computer-aided diagnosis of thyroid nodules. Since these two tasks are inherently related to each other and sharing some common features,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::856c6e577a5ba33b1e9ee6a0ce1e5fbb
https://pubmed.ncbi.nlm.nih.gov/35537340
https://pubmed.ncbi.nlm.nih.gov/35537340
Publikováno v:
Deep Generative Models, and Data Augmentation, Labelling, and Imperfections ISBN: 9783030882099
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8d3ab44cbeaf9c19d50c938288805a9a
https://doi.org/10.1007/978-3-030-88210-5_5
https://doi.org/10.1007/978-3-030-88210-5_5
Publikováno v:
DGM4MICCAI/DALI@MICCAI
Synthetic medical image generation has a huge potential for improving healthcare through many applications, from data augmentation for training machine learning systems to preserving patient privacy. Conditional Adversarial Generative Networks (cGANs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f63a327188173c0b38d4e6e1f169834
http://arxiv.org/abs/2012.04764
http://arxiv.org/abs/2012.04764
Autor:
Francis Dutil, Thomas Fevens, Qicheng Lao, Mehrzad Mortazavi, Marzieh S. Tahaei, Mohammad Havaei
In this paper, we propose a general framework in continual learning for generative models: Feature-oriented Continual Learning (FoCL). Unlike previous works that aim to solve the catastrophic forgetting problem by introducing regularization in the pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d4d0b6ff4768cf94c30a84b584e14ddc
Publikováno v:
Scopus-Elsevier
We propose a hypothesis disparity regularized mutual information maximization~(HDMI) approach to tackle unsupervised hypothesis transfer -- as an effort towards unifying hypothesis transfer learning (HTL) and unsupervised domain adaptation (UDA) -- w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5e158b8db323d089646d8d5597fae96