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H

Heng Huang

University of Pittsburgh(US)

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918

Papers

25.1K

Citations

74

h-index

389

i10-index

Heng Huang is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: Face and Expression Recognition & Stochastic Gradient Optimization Techniques & Sparse and Compressive Sensing Techniques. The author has an h-index of 74, co-authored 781 publications.

ORCID: 0000-0002-3483-8333

Research Topics

Face and Expression Recognition Stochastic Gradient Optimization Techniques Sparse and Compressive Sensing Techniques Domain Adaptation and Few-Shot Learning Machine Learning and ELM

Papers by this author

works

Multi-Pass Fast Watershed for Accurate Segmentation of Overlapping Cervical Cells

2018 · IEEE Transactions on Medical Imaging · 111 citations

https://doi.org/10.1109/tmi.2018.2815013

Afaf Tareef Yang Song Heng Huang Dagan Feng

Wavelet-Based Dual Recursive Network for Image Super-Resolution

2020 · IEEE Transactions on Neural Networks and Learning Systems · 84 citations

https://doi.org/10.1109/tnnls.2020.3028688

Jingwei Xin Jie Li Xinrui Jiang Nannan Wang

Binarized Neural Network for Single Image Super Resolution

2020 · Lecture notes in computer science · 79 citations

https://doi.org/10.1007/978-3-030-58548-8_6

Jingwei Xin Nannan Wang Xinrui Jiang Jie Li

Unsupervised Hyperbolic Metric Learning

2021 · 44 citations

https://doi.org/10.1109/cvpr46437.2021.01228

Jiexi Yan Lei Luo Cheng Deng Heng Huang

Sma- and Mad-related Protein 7 (Smad7) Is Required for Embryonic Eye Development in the Mouse

2013 · Journal of Biological Chemistry · 33 citations

https://doi.org/10.1074/jbc.m112.416719

Rui Zhang Heng Huang Peijuan Cao Zhenzhen Wang

Region-based progressive localization of cell nuclei in microscopic images with data adaptive modeling

2013 · BMC Bioinformatics · 32 citations

https://doi.org/10.1186/1471-2105-14-173

Yang Song Weidong Cai Heng Huang Yue Wang

Research topics

topics

Face and Expression Recognition

Stochastic Gradient Optimization Techniques

Sparse and Compressive Sensing Techniques

Domain Adaptation and Few-Shot Learning

Machine Learning and ELM

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