Xiaohan Yu
Orcid: 0000-0001-6186-0520Affiliations:
- Griffith University, School of Engineering, School of Engineering and Built Environment, Australia
- Wuhan University of Technology, Department of computer science and technology, China
According to our database1,
Xiaohan Yu
authored at least 59 papers
between 2014 and 2025.
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Collaborative distances:
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Bibliography
2025
Overcoming learning bias via Prototypical Feature Compensation for source-free domain adaptation.
Pattern Recognit., 2025
Uniformity and deformation: A benchmark for multi-fish real-time tracking in the farming.
Expert Syst. Appl., 2025
2024
IEEE Trans. Pattern Anal. Mach. Intell., December, 2024
ICLR: Instance Credibility-Based Label Refinement for label noisy person re-identification.
Pattern Recognit., April, 2024
Pattern Recognit., March, 2024
Towards effective person search with deep learning: A survey from systematic perspective.
Pattern Recognit., 2024
Pseudo-set Frequency Refinement architecture for fine-grained few-shot class-incremental learning.
Pattern Recognit., 2024
Knowl. Based Syst., 2024
J. Vis. Commun. Image Represent., 2024
EIANet: A Novel Domain Adaptation Approach to Maximize Class Distinction with Neural Collapse Principles.
CoRR, 2024
CoRR, 2024
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024
Proceedings of the 18th IEEE International Conference on Automatic Face and Gesture Recognition, 2024
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Proceedings of the Advanced Data Mining and Applications - 20th International Conference, 2024
2023
IEEE Trans. Artif. Intell., December, 2023
Pattern Recognit., December, 2023
Field detection of small pests through stochastic gradient descent with genetic algorithm.
Comput. Electron. Agric., March, 2023
Scale-aware stereo direct visual odometry with online photometric calibration for agricultural environment.
Adv. Robotics, March, 2023
IEEE Trans. Circuits Syst. Video Technol., February, 2023
Mix-ViT: Mixing attentive vision transformer for ultra-fine-grained visual categorization.
Pattern Recognit., 2023
Pattern Recognit., 2023
SSFE-Net: Self-Supervised Feature Enhancement for Ultra-Fine-Grained Few-Shot Class Incremental Learning.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023
Proceedings of the 38th International Conference on Image and Vision Computing New Zealand, 2023
CLE-ViT: Contrastive Learning Encoded Transformer for Ultra-Fine-Grained Visual Categorization.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2023
Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2023
SupCon-ViT: Supervised contrastive learning for ultra-fine-grained visual categorization.
Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2023
What EXACTLY are We Looking at?: Investigating for Discriminance in Ultra-Fine-Grained Visual Categorization Tasks.
Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2023
2022
Pattern Recognit., 2022
Pattern Recognit., 2022
ASRSNet: Automatic Salient Region Selection Network for Few-Shot Fine-Grained Image Classification.
Proceedings of the Pattern Recognition and Artificial Intelligence, 2022
PGTRNET: Two-Phase Weakly Supervised Object Detection with Pseudo Ground Truth Refinement.
Proceedings of the IEEE International Conference on Acoustics, 2022
Where to Focus: Investigating Hierarchical Attention Relationship for Fine-Grained Visual Classification.
Proceedings of the Computer Vision, 2022
2021
MaskCOV: A random mask covariance network for ultra-fine-grained visual categorization.
Pattern Recognit., 2021
PGTRNet: Two-phase Weakly Supervised Object Detection with Pseudo Ground Truth Refining.
CoRR, 2021
CoRR, 2021
Proceedings of the 2021 IEEE International Conference on Image Processing, 2021
Benchmark Platform for Ultra-Fine-Grained Visual Categorization Beyond Human Performance.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021
A Compositional Feature Embedding and Similarity Metric for Ultra-Fine-Grained Visual Categorization.
Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021
Mask-Guided Feature Extraction and Augmentation for Ultra-Fine-Grained Visual Categorization.
Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021
Proceedings of the 32nd British Machine Vision Conference 2021, 2021
2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
From Species to Cultivar: Soybean Cultivar Recognition using Multiscale Sliding Chord Matching of Leaf Images.
CoRR, 2019
Automatic hierarchy classification in venation networks using directional morphological filtering for hierarchical structure traits extraction.
Comput. Biol. Chem., 2019
Multiscale Contour Steered Region Integral and Its Application for Cultivar Classification.
IEEE Access, 2019
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019
2017
Proceedings of the AMIA 2017, 2017
2016
Research on campus traffic congestion detection using BP neural network and Markov model.
J. Inf. Secur. Appl., 2016
Multiscale Crossing Representation Using Combined Feature of Contour and Venation for Leaf Image Identification.
Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications, 2016
2015
An Improved Saliency Detection Approach for Flying Apsaras in the Dunhuang Grotto Murals, China.
Adv. Multim., 2015
Proceedings of the 2015 International Conference on Image and Vision Computing New Zealand, 2015
2014
Proceedings of the 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems, 2014