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Jun Han 0010
Person information
- affiliation: Chinese University of Hong Kong-Shenzhen (CUHK-SZ), Shenzhen, China
- affiliation (former): University of Notre Dame, Notre Dame, IN, USA
Other persons with the same name
- Jun Han — disambiguation page
- Jun Han 0001
— Yonsei University, School of Electrical and Electronic Engineering, Seoul, South Korea (and 2 more)
- Jun Han 0002 — Dartmouth College, USA
- Jun Han 0003
- Jun Han 0004
- Jun Han 0005
- Jun Han 0006 — Bond University, QLD, Australia
- Jun Han 0007 — University of Georgia, Athens, GA, USA
- Jun Han 0008 — University of California, San Diego, La Jolla, CA, USA
- Jun Han 0009 — Dortmund University of Technology, Germany
- Jun Han 0011 — University of Queensland, Australia
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2020 – today
- 2024
- [j14]Jun Han
KD-INR: Time-Varying Volumetric Data Compression via Knowledge Distillation-Based Implicit Neural Representation. IEEE Trans. Vis. Comput. Graph. 30(10): 6826-6838 (2024) - 2023
- [j13]Siyuan Yao
GMT: A deep learning approach to generalized multivariate translation for scientific data analysis and visualization. Comput. Graph. 112: 92-104 (2023) - [j12]Chaoli Wang
DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization. IEEE Trans. Vis. Comput. Graph. 29(8): 3714-3733 (2023) - [j11]Jun Han
CoordNet: Data Generation and Visualization Generation for Time-Varying Volumes via a Coordinate-Based Neural Network. IEEE Trans. Vis. Comput. Graph. 29(12): 4951-4963 (2023) - 2022
- [j10]Jun Han, Chaoli Wang:
TSR-VFD: Generating temporal super-resolution for unsteady vector field data. Comput. Graph. 103: 168-179 (2022) - [j9]Jun Han
SurfNet: Learning Surface Representations via Graph Convolutional Network. Comput. Graph. Forum 41(3): 109-120 (2022) - [j8]Jun Han, Hao Zheng
STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes. IEEE Trans. Vis. Comput. Graph. 28(1): 270-280 (2022) - [j7]Jun Han
SSR-TVD: Spatial Super-Resolution for Time-Varying Data Analysis and Visualization. IEEE Trans. Vis. Comput. Graph. 28(6): 2445-2456 (2022) - [j6]Jun Han, Chaoli Wang:
VCNet: A generative model for volume completion. Vis. Informatics 6(2): 62-73 (2022) - [c11]Pengfei Gu, Jun Han, Danny Z. Chen, Chaoli Wang:
Scalar2Vec: Translating Scalar Fields to Vector Fields via Deep Learning. PacificVis 2022: 31-40 - [c10]Reshika Palaniyappan Velumani, Meng Xia
AQX: Explaining Air Quality Forecast for Verifying Domain Knowledge using Feature Importance Visualization. IUI 2022: 720-733 - [i2]Chaoli Wang, Jun Han:
DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization. CoRR abs/2204.06504 (2022) - 2021
- [j5]Pengfei Gu
Reconstructing Unsteady Flow Data From Representative Streamlines via Diffusion and Deep-Learning-Based Denoising. IEEE Computer Graphics and Applications 41(6): 111-121 (2021) - [j4]Jun Han
V2V: A Deep Learning Approach to Variable-to-Variable Selection and Translation for Multivariate Time-Varying Data. IEEE Trans. Vis. Comput. Graph. 27(2): 1290-1300 (2021) - [c9]Hao Zheng
Hierarchical Self-supervised Learning for Medical Image Segmentation Based on Multi-domain Data Aggregation. MICCAI (1) 2021: 622-632 - [i1]Hao Zheng, Jun Han, Hongxiao Wang, Lin Yang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen:
Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation. CoRR abs/2107.04886 (2021) - 2020
- [j3]Jun Han, Chaoli Wang:
TSR-TVD: Temporal Super-Resolution for Time-Varying Data Analysis and Visualization. IEEE Trans. Vis. Comput. Graph. 26(1): 205-215 (2020) - [j2]Jun Han
FlowNet: A Deep Learning Framework for Clustering and Selection of Streamlines and Stream Surfaces. IEEE Trans. Vis. Comput. Graph. 26(4): 1732-1744 (2020) - [c8]Li Guo, Shaojie Ye, Jun Han, Hao Zheng, Han Gao, Danny Z. Chen, Jian-Xun Wang, Chaoli Wang:
SSR-VFD: Spatial Super-Resolution for Vector Field Data Analysis and Visualization. PacificVis 2020: 71-80 - [c7]Yang Zhang, Xiangyu Dong, Md. Tahmid Rashid
PQA-CNN: Towards Perceptual Quality Assured Single-Image Super-Resolution in Remote Sensing. IWQoS 2020: 1-10 - [c6]Yang Zhang, Ruohan Zong, Jun Han, Daniel Zhang, Md. Tahmid Rashid
TransRes: A Deep Transfer Learning Approach to Migratable Image Super-Resolution in Remote Urban Sensing. SECON 2020: 1-9
2010 – 2019
- 2019
- [j1]Jun Han, Jun Tao, Hao Zheng, Hanqi Guo
Flow Field Reduction Via Reconstructing Vector Data From 3-D Streamlines Using Deep Learning. IEEE Computer Graphics and Applications 39(4): 54-67 (2019) - [c5]Hao Zheng
Biomedical Image Segmentation via Representative Annotation. AAAI 2019: 5901-5908 - [c4]Yang Zhang, Ruohan Zong, Jun Han, Hao Zheng, Qiuwen Lou, Daniel Yue Zhang, Dong Wang:
TransLand: An Adversarial Transfer Learning Approach for Migratable Urban Land Usage Classification using Remote Sensing. IEEE BigData 2019: 1567-1576 - [c3]Martin Imre, Jun Han, Julien Dominski
ContourNet: Salient Local Contour Identification for Blob Detection in Plasma Fusion Simulation Data. ISVC (1) 2019: 289-301 - [c2]Hao Zheng
HFA-Net: 3D Cardiovascular Image Segmentation with Asymmetrical Pooling and Content-Aware Fusion. MICCAI (2) 2019: 759-767 - [c1]William P. Porter, Yunhao Xing, Blaise R. von Ohlen, Jun Han, Chaoli Wang:
A Deep Learning Approach to Selecting Representative Time Steps for Time-Varying Multivariate Data. IEEE VIS (Short Papers) 2019: 131-135
Coauthor Index
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last updated on 2024-12-10 21:41 CET by the dblp team
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