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Ze Jin
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2020 – today
- 2024
- [j11]Chunwen Liu, Ru Tan, Yang Wu, Yun Feng, Ze Jin, Fangjiao Zhang, Yuling Liu, Qixu Liu:
Dissecting zero trust: research landscape and its implementation in IoT. Cybersecur. 7(1): 20 (2024) - [j10]Ke Yang, Jizheng Yi
, Aibin Chen, Ze Jin:
Buffer-text: Detecting arbitrary shaped text in natural scene image. Eng. Appl. Artif. Intell. 130: 107774 (2024) - [j9]Junsong Chen, Jizheng Yi
SMFE-Net: a saliency multi-feature extraction framework for VHR remote sensing image classification. Multim. Tools Appl. 83(2): 3831-3854 (2024) - [j8]Ze Jin, Taehyun Hwang, Daehoon Kim, Byounghyun Lim, Oh-Seok Kwon
Anti- and pro-fibrillatory effects of pulmonary vein isolation gaps in human atrial fibrillation digital twins. npj Digit. Medicine 7(1) (2024) - [c22]Yuqiao Yang, Ze Jin, Fumihiko Nakatani, Mototaka Miyake, Kenji Suzuki:
"Small-data" Patch-wise Multi-dimensional Output Deep-learning for Rare Cancer Diagnosis in MRI under Limited Sample-size Situation. ISBI 2024: 1-4 - [c21]Shogo Kodera
Super-Efficient Lung Nodule Classification Using Massive-Training Artificial Neural Network (MTANN) Compact Model on LIDC-IDRI Database. IVSP 2024: 213-220 - 2023
- [j7]Taeyoon Kim, Chanho Park, Mansur Mukimbekov, Heelim Hong, Minseok Kim, Ze Jin, Changdae Kim, Ji-Yong Shin, Myeongjae Jeon:
FusionFlow: Accelerating Data Preparation for Machine Learning with Hybrid CPU-GPU Processing. Proc. VLDB Endow. 17(4): 863-876 (2023) - [j6]Junsong Chen
EFCOMFF-Net: A Multiscale Feature Fusion Architecture With Enhanced Feature Correlation for Remote Sensing Image Scene Classification. IEEE Trans. Geosci. Remote. Sens. 61: 1-17 (2023) - [c20]Xinyu Liu
ANDetect: A Third-party Ad Network Libraries Detection Framework for Android Applications. ACSAC 2023: 98-112 - [c19]Xingchen Chen, Baizhu Wang, Ze Jin, Yun Feng, Xianglong Li, Xincheng Feng, Qixu Liu:
Tabby: Automated Gadget Chain Detection for Java Deserialization Vulnerabilities. DSN 2023: 179-192 - [c18]Zhipeng Deng
Radiation Dose Reduction in Digital Breast Tomosynthesis by MTANN with Multi-scale Kernels. EMBC 2023: 1-7 - [c17]Ze Jin, Maolin Pang, Yuqiao Yang, Fahad Parvez Mahdi, Tianyi Qu, Ren Sasage, Kenji Suzuki
Explaining Massive-Training Artificial Neural Networks in Medical Image Analysis Task Through Visualizing Functions Within the Models. MICCAI (2) 2023: 713-722 - [c16]Xu Lei, Fahad Parvez Mahdi, Ze Jin, Hao Sun, Yoshiyuki Noguchi, Masayuki Murata, Kenji Suzuki:
Generating simulated fluorescence images for enhancing proteins from optical microscopy images of cells using massive-training artificial neural networks. Digital and Computational Pathology 2023 - [i2]Ze Jin, Zorina Song:
Generating coherent comic with rich story using ChatGPT and Stable Diffusion. CoRR abs/2305.11067 (2023) - 2022
- [j5]Ke Yang
ConvPatchTrans: A script identification network with global and local semantics deeply integrated. Eng. Appl. Artif. Intell. 113: 104916 (2022) - [c15]Ze Jin, Luyi Xing, Yiwei Fang, Yan Jia
P-Verifier: Understanding and Mitigating Security Risks in Cloud-based IoT Access Policies. CCS 2022: 1647-1661 - [c14]Yuqiao Yang, Ze Jin, Kenji Suzuki
Federated Tumor Segmentation with Patch-Wise Deep Learning Model. MLMI@MICCAI 2022: 456-465 - [c13]Zhipeng Deng
FedAL: An Federated Active Learning Framework for Efficient Labeling in Skin Lesion Analysis. SMC 2022: 1554-1559 - 2021
- [j4]Yi Sima
Automatic expression recognition of face image sequence based on key-frame generation and differential emotion feature. Appl. Soft Comput. 113(Part): 108029 (2021) - [c12]Muneyuki Sato, Ze Jin, Kenji Suzuki
Semantic Segmentation of Liver Tumor in Contrast-enhanced Hepatic CT by Using Deep Learning with Hessian-based Enhancer with Small Training Dataset Size. ISBI 2021: 34-37 - [c11]Maodong Xiang, Ze Jin, Kenji Suzuki
Massive-Training Artificial Neural Network (Mtann) With Special Kernel For Artifact Reduction In Fast-Acquisition Mri Of The Knee. ISBI 2021: 1210-1213 - 2020
- [c10]Gangmuk Lim, Mohamed S. Hassan, Ze Jin, Stavros Volos, Myeongjae Jeon:
Approximate Quantiles for Datacenter Telemetry Monitoring. ICDE 2020: 1914-1917 - [c9]Ze Jin, Jayaram K. Udupa, Drew A. Torigian:
Obtaining the potential number of object models/atlases needed in medical image analysis. Image-Guided Procedures 2020: 1131533
2010 – 2019
- 2019
- [j3]Ze Jin, Jayaram K. Udupa, Drew A. Torigian:
How many models/atlases are needed as priors for capturing anatomic population variations? Medical Image Anal. 58 (2019) - [j2]Ze Jin
Optimization and testing in linear non-Gaussian component analysis. Stat. Anal. Data Min. 12(3): 141-156 (2019) - [c8]Yuchen Wang, Ze Jin, Yukiko Tokuda, Yasuto Naoi, Noriyuki Tomiyama, Kenji Suzuki
Development of Deep-learning Segmentation for Breast Cancer in MR Images based on Neural Network Convolution. ICCPR 2019: 187-191 - [c7]Ze Jin, David S. Matteson
Independent Component Analysis Based on Mutual Dependence Measures. ICMLA 2019: 573-580 - [c6]Ze Jin, Jayaram K. Udupa, Drew A. Torigian:
Obtaining the potential number of models/atlases needed for capturing anatomic variations in population images. Image Processing 2019: 109493G - [c5]Cheng Tan, Ze Jin, Chuanxiong Guo, Tianrong Zhang, Haitao Wu, Karl Deng, Dongming Bi, Dong Xiang:
NetBouncer: Active Device and Link Failure Localization in Data Center Networks. NSDI 2019: 599-614 - [i1]Gangmuk Lim, Mohamed S. Hassan, Ze Jin, Stavros Volos, Myeongjae Jeon:
Approximate Quantiles for Datacenter Telemetry Monitoring. CoRR abs/1906.00228 (2019) - 2018
- [j1]Ze Jin
Generalizing distance covariance to measure and test multivariate mutual dependence via complete and incomplete V-statistics. J. Multivar. Anal. 168: 304-322 (2018) - [c4]Ze Jin, Xiaohan Yan, David S. Matteson:
Testing for Conditional Mean Independence with Covariates through Martingale Difference Divergence. UAI 2018: 1-12 - 2016
- [c3]Paul Raff, Ze Jin:
The difference-of-datasets framework: A statistical method to discover insight. IEEE BigData 2016: 1824-1831 - 2015
- [c2]Caiya Zhang, Ze Jin:
Initial Seeds Selection in Dynamic Clustering Method Based on Data Depth. IScIDE (2) 2015: 603-611 - 2013
- [c1]Hidetaka Arimura, Ze Jin, Yoshiyuki Shioyama, Katsumasa Nakamura, Taiki Magome, Masayuki Sasaki:
Automated method for extraction of lung tumors using a machine learning classifier with knowledge of radiation oncologists on data sets of planning CT and FDG-PET/CT images. EMBC 2013: 2988-2991
Coauthor Index
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last updated on 2024-12-08 01:29 CET by the dblp team
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