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Gang Niu

Showing results (171-180 of 583) with videos related to

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Theranostics|October 7, 2014
Quantitative proteomics analysis identifies mitochondria as therapeutic targets of multidrug-resistance in ovarian cancerXiulan Chen, Shasha Wei, Ying Ma, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 31, 2022
Class-Wise Denoising for Robust Learning Under Label NoiseChen Gong, Yongliang Ding, Bo Han, et al.
Journal of Hazardous Materials|October 3, 2021
Metal-organic framework-derived CuCo/carbon as an efficient magnetic heterogeneous catalyst for persulfate activation and ciprofloxacin degradationMing-Ming Chen, Huai-Yuan Niu, Cheng-Gang Niu, et al.
Academic Radiology|June 2, 2019
Clinical Applications of DSC-MRI Parameters Assess Angiogenesis and Differentiate Malignant From Benign Soft Tissue Tumors in LimbsYitong Bian, Ping Jin, Yanliang Wang, et al.
Chemical Communications (Cambridge, England)|August 25, 2012
A nanoscale graphene oxide-peptide biosensor for real-time specific biomarker detection on the cell surfaceZhe Wang, Peng Huang, Ashwinkumar Bhirde, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 13, 2026
Instance-dependent Early Stopping for Adaptive Data PruningSuqin Yuan, Runqi Lin, Felix Azian, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|August 4, 2023
A Parametrical Model for Instance-Dependent Label NoiseShuo Yang, Songhua Wu, Erkun Yang, et al.
Journal of Fungi (Basel, Switzerland)|September 28, 2021
FgSfl1 and Its Conserved PKA Phosphorylation Sites Are Important for Conidiation, Sexual Reproduction, and Pathogenesis in <i>Fusarium graminearum</i>Chen Gong, Junqi Huang, Daiyuan Sun, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|September 23, 2024
Estimating Per-Class Statistics for Label Noise LearningWenshui Luo, Shuo Chen, Tongliang Liu, et al.
Nanoscale Research Letters|April 17, 2013
Self-assembly of gold nanoparticles to silver microspheres as highly efficient 3D SERS substratesShouhui Chen, Peng Huang, Zhihua Wang, et al.
Pageof 59

Showing results (171-180 of 583) with videos related to

Sort By:
Pageof 59
Theranostics|October 7, 2014
Quantitative proteomics analysis identifies mitochondria as therapeutic targets of multidrug-resistance in ovarian cancerXiulan Chen, Shasha Wei, Ying Ma, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 31, 2022
Class-Wise Denoising for Robust Learning Under Label NoiseChen Gong, Yongliang Ding, Bo Han, et al.
Journal of Hazardous Materials|October 3, 2021
Metal-organic framework-derived CuCo/carbon as an efficient magnetic heterogeneous catalyst for persulfate activation and ciprofloxacin degradationMing-Ming Chen, Huai-Yuan Niu, Cheng-Gang Niu, et al.
Academic Radiology|June 2, 2019
Clinical Applications of DSC-MRI Parameters Assess Angiogenesis and Differentiate Malignant From Benign Soft Tissue Tumors in LimbsYitong Bian, Ping Jin, Yanliang Wang, et al.
Chemical Communications (Cambridge, England)|August 25, 2012
A nanoscale graphene oxide-peptide biosensor for real-time specific biomarker detection on the cell surfaceZhe Wang, Peng Huang, Ashwinkumar Bhirde, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 13, 2026
Instance-dependent Early Stopping for Adaptive Data PruningSuqin Yuan, Runqi Lin, Felix Azian, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|August 4, 2023
A Parametrical Model for Instance-Dependent Label NoiseShuo Yang, Songhua Wu, Erkun Yang, et al.
Journal of Fungi (Basel, Switzerland)|September 28, 2021
FgSfl1 and Its Conserved PKA Phosphorylation Sites Are Important for Conidiation, Sexual Reproduction, and Pathogenesis in <i>Fusarium graminearum</i>Chen Gong, Junqi Huang, Daiyuan Sun, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|September 23, 2024
Estimating Per-Class Statistics for Label Noise LearningWenshui Luo, Shuo Chen, Tongliang Liu, et al.
Nanoscale Research Letters|April 17, 2013
Self-assembly of gold nanoparticles to silver microspheres as highly efficient 3D SERS substratesShouhui Chen, Peng Huang, Zhihua Wang, et al.
Pageof 59