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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1958 1
1964 1
1970 1
1971 1
1972 3
1973 1
1974 2
1975 9
1976 9
1977 5
1978 8
1979 7
1980 7
1981 9
1982 14
1983 18
1984 9
1985 23
1986 18
1987 11
1988 23
1989 20
1990 13
1991 30
1992 22
1993 30
1994 34
1995 26
1996 45
1997 33
1998 32
1999 40
2000 41
2001 40
2002 51
2003 87
2004 98
2005 104
2006 126
2007 163
2008 179
2009 178
2010 195
2011 216
2012 255
2013 247
2014 269
2015 299
2016 297
2017 339
2018 372
2019 494
2020 598
2021 790
2022 901
2023 932
2024 485

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Search Results

7,445 results

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Page 1
Showing results for manual labels
Search for Manuel Abels instead (2 results)
Cross-modal hashing with missing labels.
Ni H, Zhang J, Kang P, Fang X, Sun W, Xie S, Han N. Ni H, et al. Neural Netw. 2023 Aug;165:60-76. doi: 10.1016/j.neunet.2023.05.035. Epub 2023 May 24. Neural Netw. 2023. PMID: 37276811
There are two reasons for this, as manual labeling can be a complex and time-consuming task, and annotators may only be interested in certain objects. ...The representation of samples is extracted from different modalities, which assists in inferring missing labe …
There are two reasons for this, as manual labeling can be a complex and time-consuming task, and annotators may only be intere …
Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation.
Letunic I, Bork P. Letunic I, et al. Nucleic Acids Res. 2021 Jul 2;49(W1):W293-W296. doi: 10.1093/nar/gkab301. Nucleic Acids Res. 2021. PMID: 33885785 Free PMC article.
Node metadata display options have been extended and now also support non-numerical categorical values, as well as multiple values per node. Direct manual annotation is now available, providing a set of basic drawing and labeling tools, allowing users to draw shapes …
Node metadata display options have been extended and now also support non-numerical categorical values, as well as multiple values per node. …
Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.
Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM. Fischl B, et al. Neuron. 2002 Jan 31;33(3):341-55. doi: 10.1016/s0896-6273(02)00569-x. Neuron. 2002. PMID: 11832223 Free article.
We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set. In contrast to existing segmentation procedures that onl …
We present a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic info …
Sparsely-Supervised Object Tracking.
Zheng J, Li W, Ma C, Yang X. Zheng J, et al. IEEE Trans Image Process. 2024;33:3470-3485. doi: 10.1109/TIP.2024.3404257. Epub 2024 Jun 4. IEEE Trans Image Process. 2024. PMID: 38809731
Despite the success, these trackers require millions of sequential manual labels on videos for supervised training, implying the heavy burden of human annotating. ...Moreover, our SPOT exhibits two desirable properties: 1) SPOT enables us to fully exploit large-scal …
Despite the success, these trackers require millions of sequential manual labels on videos for supervised training, implying t …
Intra-oral scan segmentation using deep learning.
Vinayahalingam S, Kempers S, Schoep J, Hsu TH, Moin DA, van Ginneken B, Flügge T, Hanisch M, Xi T. Vinayahalingam S, et al. BMC Oral Health. 2023 Sep 5;23(1):643. doi: 10.1186/s12903-023-03362-8. BMC Oral Health. 2023. PMID: 37670290 Free PMC article.
This study aims to develop an automated teeth segmentation and labeling system using deep learning. MATERIAL AND METHODS: As a reference, 1750 OS were manually segmented and labeled. ...RESULTS: The model achieved accurate teeth segmentations with a mean IoU …
This study aims to develop an automated teeth segmentation and labeling system using deep learning. MATERIAL AND METHODS: As a refere …
Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims: draft guidance.
U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research; U.S. Department of Health and Human Services FDA Center for Biologics Evaluation and Research; U.S. Department of Health and Human Services FDA Center for Devices and Radiological Health. U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research, et al. Health Qual Life Outcomes. 2006 Oct 11;4:79. doi: 10.1186/1477-7525-4-79. Health Qual Life Outcomes. 2006. PMID: 17034633 Free PMC article.
It also describes our current thinking on how sponsors can develop and use study results measured by PRO instruments to support claims in approved product labeling (see appendix point 1). It does not address the use of PRO instruments for purposes beyond evaluation …
It also describes our current thinking on how sponsors can develop and use study results measured by PRO instruments to support claims in ap …
Prediction of common labels for universal domain adaptation.
Shan X, Ma T, Wen Y. Shan X, et al. Neural Netw. 2023 Aug;165:463-471. doi: 10.1016/j.neunet.2023.05.057. Epub 2023 Jun 7. Neural Netw. 2023. PMID: 37336031
Universal domain adaptation (UniDA) is an unsupervised domain adaptation that selectively transfers the knowledge between different domains containing different label sets. However, the existing methods do not predict the common labels of different domains and ma …
Universal domain adaptation (UniDA) is an unsupervised domain adaptation that selectively transfers the knowledge between different domains …
Collaborative learning with corrupted labels.
Wang Y, Huang R, Huang G, Song S, Wu C. Wang Y, et al. Neural Netw. 2020 May;125:205-213. doi: 10.1016/j.neunet.2020.02.010. Epub 2020 Feb 26. Neural Netw. 2020. PMID: 32145649
However, their high generalization performance often comes with the high cost of annotating data manually. Collecting low-quality labeled dataset is relatively cheap, e.g., using web search engines, while DNNs tend to overfit to corrupted labels easily. ...Co …
However, their high generalization performance often comes with the high cost of annotating data manually. Collecting low-quality …
FDA-approved drugs that interfere with laboratory tests: A systematic search of US drug labels.
Yao H, Rayburn ER, Shi Q, Gao L, Hu W, Li H. Yao H, et al. Crit Rev Clin Lab Sci. 2017 Jan;54(1):1-17. doi: 10.1080/10408363.2016.1191425. Epub 2016 Jun 27. Crit Rev Clin Lab Sci. 2017. PMID: 27193822 Review.
Although there have been numerous reports about specific drugs that interfere with laboratory tests, there has not been a recent review on the topic. We herein provide a review of the known DLTI of US FDA-approved drugs based on a systematic search of DailyMed, a website c …
Although there have been numerous reports about specific drugs that interfere with laboratory tests, there has not been a recent review on t …
Anti-Interference From Noisy Labels: Mean-Teacher-Assisted Confident Learning for Medical Image Segmentation.
Xu Z, Lu D, Luo J, Wang Y, Yan J, Ma K, Zheng Y, Tong RK. Xu Z, et al. IEEE Trans Med Imaging. 2022 Nov;41(11):3062-3073. doi: 10.1109/TMI.2022.3176915. Epub 2022 Oct 27. IEEE Trans Med Imaging. 2022. PMID: 35604969
As a result, we are often forced to collect additional labeled data from multiple sources with varying label qualities. However, directly introducing additional data with low-quality noisy labels may mislead the network training and undesirably offset the eff …
As a result, we are often forced to collect additional labeled data from multiple sources with varying label qualities. Howeve …
7,445 results