Search Results for author: Sy-Yen Kuo

Found 8 papers, 7 papers with code

Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise

no code implementations2 Nov 2022 Jhih-Cing Huang, Yu-Lin Tsai, Chao-Han Huck Yang, Cheng-Fang Su, Chia-Mu Yu, Pin-Yu Chen, Sy-Yen Kuo

Recently, quantum classifiers have been known to be vulnerable to adversarial attacks, where quantum classifiers are fooled by imperceptible noises to have misclassification.

RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning

1 code implementation18 Sep 2022 Wei-Ting Chen, I-Hsiang Chen, Chih-Yuan Yeh, Hao-Hsiang Yang, Hua-En Chang, Jian-Jiun Ding, Sy-Yen Kuo

Recently, vehicle similarity learning, also called re-identification (ReID), has attracted significant attention in computer vision.

Learning Multiple Adverse Weather Removal via Two-Stage Knowledge Learning and Multi-Contrastive Regularization: Toward a Unified Model

1 code implementation CVPR 2022 Wei-Ting Chen, Zhi-Kai Huang, Cheng-Che Tsai, Hao-Hsiang Yang, Jian-Jiun Ding, Sy-Yen Kuo

At the KC, the student network aims to learn the comprehensive bad weather removal problem from multiple well-trained teacher networks where each of them is specialized in a specific bad weather removal problem.

Transfer Learning

Multi-modal Bifurcated Network for Depth Guided Image Relighting

1 code implementation3 May 2021 Hao-Hsiang Yang, Wei-Ting Chen, Hao-Lun Luo, Sy-Yen Kuo

This model extracts the image and the depth features by the bifurcated network in the encoder.

Image Relighting SSIM

ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel Loss

1 code implementation ICCV 2021 Wei-Ting Chen, Hao-Yu Fang, Cheng-Lin Hsieh, Cheng-Che Tsai, I-Hsiang Chen, Jian-Jiun Ding, Sy-Yen Kuo

Moreover, due to the limitation of existing snow datasets, to simulate the snow scenarios comprehensively, we propose a large-scale dataset called Comprehensive Snow Dataset (CSD).

Single Image Desnowing

PMHLD: Patch Map Based Hybrid Learning DehazeNet for Single Image Haze Removal

1 code implementation IEEE Transaction on Image Processing 2020 Wei-Ting Chen, Hao-Yu Feng, Jian-Jiun Ding, Sy-Yen Kuo

In addition, to further enhance the performance of the method for haze removal, a patch-map-based DCP has been embedded into the network, and this module has been trained with the atmospheric light generator, patch map selection module, and refined module simultaneously.

Computational Phenotyping Denoising +5

Cannot find the paper you are looking for? You can Submit a new open access paper.