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Learning Discriminative Neural Sentiment Units for Semi-supervised Target-Level Sentiment Classification.

J. Zhao, Y. Yang, G. Pang, L. Lv, H. Shang, Z. Sun, and W. Yang. PAKDD (2), volume 12085 of Lecture Notes in Computer Science, page 798-810. Springer, (2020)

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Li Shang

Huiping Shang

Heping Shang

Xiaolei Shang

Dongkai Shangguan

Other publications of authors with the same name

Weakly Supervised Learning with Side Information for Noisy Labeled Images.L. Cheng, X. Zhou, L. Zhao, D. Li, H. Shang, Y. Zheng, P. Pan, and Y. Xu. ECCV (30), volume 12375 of Lecture Notes in Computer Science, page 306-321. Springer, (2020)3D Brain Midline Delineation for Hematoma Patients.C. Qin, H. Li, Y. Liu, H. Shang, H. Pei, X. Wang, Y. Chen, J. Chang, M. Feng, R. Wang and 1 other author(s). MICCAI (5), volume 12905 of Lecture Notes in Computer Science, page 510-518. Springer, (2021)Leveraging Other Datasets for Medical Imaging Classification: Evaluation of Transfer, Multi-task and Semi-supervised Learning.H. Shang, Z. Sun, W. Yang, X. Fu, H. Zheng, J. Chang, and J. Huang. MICCAI (5), volume 11768 of Lecture Notes in Computer Science, page 431-439. Springer, (2019)High Resolution $^13$C MRI With Hyperpolarized Urea: In Vivo $T_2$ Mapping and $^15$N Labeling Effects.G. Reed, C. von Morze, R. Bok, B. Koelsch, M. Criekinge, K. Smith, H. Shang, P. Larson, J. Kurhanewicz, and D. Vigneron. IEEE Trans. Med. Imaging, 33 (2): 362-371 (2014)ASM: Adaptive Skinning Model for High-Quality 3D Face Modeling.K. Yang, H. Shang, T. Shi, X. Chen, J. Zhou, Z. Sun, and W. Yang. ICCV, page 20651-20660. IEEE, (2023)What And How Other Datasets Can Be Leveraged For Medical Imaging Classification.H. Shang, Z. Sun, X. Fu, Z. Zhang, and W. Yang. ISBI, page 814-818. IEEE, (2019)Intracerebral Haemorrhage Growth Prediction Based on Displacement Vector Field and Clinical Metadata.T. Xiao, H. Zheng, X. Wang, X. Chen, J. Chang, J. Yao, H. Shang, and P. Liu. MICCAI (5), volume 12905 of Lecture Notes in Computer Science, page 741-751. Springer, (2021)Learning Discriminative Neural Sentiment Units for Semi-supervised Target-Level Sentiment Classification.J. Zhao, Y. Yang, G. Pang, L. Lv, H. Shang, Z. Sun, and W. Yang. PAKDD (2), volume 12085 of Lecture Notes in Computer Science, page 798-810. Springer, (2020)Asynchronous in Parallel Detection and Tracking (AIPDT): Real-Time Robust Polyp Detection.Z. Zhang, H. Shang, H. Zheng, X. Wang, J. Wang, Z. Sun, J. Huang, and J. Yao. MICCAI (3), volume 12263 of Lecture Notes in Computer Science, page 722-731. Springer, (2020)The analysis of errors for field experiment based on POV-Ray.H. Shang, F. Zhao, and H. Zhao. IGARSS, page 4805-4808. IEEE, (2012)

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Disambiguation of "Shang, Hong"

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Learning Discriminative Neural Sentiment Units for Semi-supervised Target-Level Sentiment Classification.

Please choose a person to relate this publication to

Li Shang

Huiping Shang

Heping Shang

Xiaolei Shang

Dongkai Shangguan

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Shang, Hong"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Learning Discriminative Neural Sentiment Units for Semi-supervised Target-Level Sentiment Classification.

Please choose a person to relate this publication to

Li Shang

Huiping Shang

Heping Shang

Xiaolei Shang

Dongkai Shangguan

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Learning Discriminative Neural Sentiment Units for Semi-supervised Target-Level Sentiment Classification.