Qingji Guan
Orcid: 0000-0002-0155-940X
According to our database1,
Qingji Guan
authored at least 21 papers
between 2018 and 2025.
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Bibliography
2025
ReFrame: A Resource-Friendly Cloud-Assisted On-Device Deep Learning Framework for Vision Services.
IEEE Trans. Serv. Comput., 2025
IEEE Trans. Multim., 2025
CLIP-driven Coarse-to-fine Semantic Guidance for Fine-grained Open-set Semi-supervised Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025
2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
A Hard Knowledge Regularization Method with Probability Difference in Thorax Disease Images.
Knowl. Based Syst., October, 2023
Image Vis. Comput., September, 2023
An Improved Heteroscedastic Modeling Method for Chest X-ray Image Classification with Noisy Labels.
Algorithms, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Learning From Pixel-Level Label Noise: A New Perspective for Semi-Supervised Semantic Segmentation.
IEEE Trans. Image Process., 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
Discriminative Feature Learning for Thorax Disease Classification in Chest X-ray Images.
IEEE Trans. Image Process., 2021
RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
2020
Object Discovery From a Single Unlabeled Image by Mining Frequent Itemsets With Multi-Scale Features.
IEEE Trans. Image Process., 2020
Pattern Recognit. Lett., 2020
Multi-label chest X-ray image classification via category-wise residual attention learning.
Pattern Recognit. Lett., 2020
J. Vis. Commun. Image Represent., 2020
2019
Mining Objects: Fully Unsupervised Object Discovery and Localization From a Single Image.
CoRR, 2019
2018
Diagnose like a Radiologist: Attention Guided Convolutional Neural Network for Thorax Disease Classification.
CoRR, 2018
GraphNet: Learning Image Pseudo Annotations for Weakly-Supervised Semantic Segmentation.
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018