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Proceedings of the 27th ACM International Conference on Multimedia, 2019
Face frontalization has always been an important field. Recently, with the introduction of generative adversarial networks (GANs), face frontalization has achieved remarkable success. A critical challenge during face frontalization is to ensure the features of the original profile image are retained.
Juntong Cheng +3 more
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Face frontalization has always been an important field. Recently, with the introduction of generative adversarial networks (GANs), face frontalization has achieved remarkable success. A critical challenge during face frontalization is to ensure the features of the original profile image are retained.
Juntong Cheng +3 more
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2020
?????????????????????? ?????????????????????? ?????????????????????? ???????????????????????????????? ???????????????? Tc(C) ?? ???? ?????????????????????? (1/Tc)(???Tc/???P)(C) ???? ???????????????????? ?????????????? ?????????????????? ?? ?????????????? Re1?????Mo??. ???????????????????? ???????????????????? ???????????????????? Tc ?? ?????????????? ?
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?????????????????????? ?????????????????????? ?????????????????????? ???????????????????????????????? ???????????????? Tc(C) ?? ???? ?????????????????????? (1/Tc)(???Tc/???P)(C) ???? ???????????????????? ?????????????? ?????????????????? ?? ?????????????? Re1?????Mo??. ???????????????????? ???????????????????? ???????????????????? Tc ?? ?????????????? ?
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2021
???????????????????????? ?????????????????????? ?????????????????? ?????????????????????? ???????????????????????????????? ???????????????? ?? ???????? ???????????????? ?? ?????????????????? ???????????????? ?????????????????????? ???????????????????????????? ?????? ?????????????????? ???????????????? ????????????????.
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???????????????????????? ?????????????????????? ?????????????????? ?????????????????????? ???????????????????????????????? ???????????????? ?? ???????? ???????????????? ?? ?????????????????? ???????????????? ?????????????????????? ???????????????????????????? ?????? ?????????????????? ???????????????? ????????????????.
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Uranyl-Tc(
Pertechnetate ( 99 Tc VII O 4 − ) and autoreduced 99 Tc( v ), species coordinate to UO 2
Mohammad Shohel, May Nyman
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Proceedings of the 19th ACM international conference on Information and knowledge management, 2010
The text classification methods heavily depend on machine learning algorithms with abstract mathematic metrics, which obstruct the direct observation and intuitive understanding of the text-specific classification. In this paper, we model a document as a Document-Classes-Topics top-down hierarchical structure.
Wenbo Li +4 more
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The text classification methods heavily depend on machine learning algorithms with abstract mathematic metrics, which obstruct the direct observation and intuitive understanding of the text-specific classification. In this paper, we model a document as a Document-Classes-Topics top-down hierarchical structure.
Wenbo Li +4 more
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Levels in ⁹⁷Tc , ⁹⁹Tc , ¹⁰¹Tc and ¹⁰¹Ru
1972Levels in ⁹⁷Tc , ⁹⁹Tc , ¹⁰¹Tc and ¹⁰¹Ru have been studied using the electron-capture decay of ⁹⁷Ru and the beta decays of ⁹⁹Mo, ¹⁰¹Mo and ¹⁰¹Tc, respectively. The energies and intensities of the gamma rays involved in these decays were measured with high precision by Ge(Li) detectors.
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1998
The four test cases comprise the backfacing step at high Re-number (TC-2A) and low Re-number (TC-2B), a low Re-number boundary layer flow past a thin obstacle, fence-on-wall (TC-2C), and a high Re-number developed channel flow past a square obstacle (TC-2D). Geometry, test conditions and available data are described.
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The four test cases comprise the backfacing step at high Re-number (TC-2A) and low Re-number (TC-2B), a low Re-number boundary layer flow past a thin obstacle, fence-on-wall (TC-2C), and a high Re-number developed channel flow past a square obstacle (TC-2D). Geometry, test conditions and available data are described.
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TC-99M GALACTOSYL-NEOGLYCOALBUMIN (TC-NGA)
Clinical Nuclear Medicine, 1983Robert C. Stadalnik +6 more
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???? ???????????????????????????? ?????????????????? ?????????????? Tc I
2023?????????????????? ?????????????????? ?????????????? ?????????? ???????????????? ?? ???????????????? ?????????? ?? ????????????. ?????????????? ?????????????????????? ?? ?????????????????????????? ?????????????????? ?????????????????? ???????????? ???????????????????????????????????? ???????? ???????????? ??? ???????? ?????? ????????????????????????????
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