Xiaohong Han
Orcid: 0000-0002-8779-6528
According to our database1,
Xiaohong Han authored at least 20 papers
between 2020 and 2026.
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Bibliography
2026
DualAdapt : A simple parallel framework makes CLIP-based Few-shot Learning classifier see better.
J. Vis. Commun. Image Represent., 2026
J. Biomed. Informatics, 2026
2025
DPEfficR: a data and parameter efficient approach for training neural API recommendation model.
Autom. Softw. Eng., November, 2025
Multi-Task Network Guided by Ultrasound Features for Predicting BRAF<sup>V600E</sup> Mutation Status in Thyroid Ultrasound Images.
Int. J. Imaging Syst. Technol., 2025
A Novel IgG-IgM Autoantibody Panel Enhances Detection of Early-stage Lung Adenocarcinoma from Benign Nodules.
Genom. Proteom. Bioinform., 2025
MINet: A Pedestrian Trajectory Forecasting Method with Multi-Information Feature Fusion.
Comput. Informatics, 2025
Lightweight Dual-Stream Human Behavior Inference Network Based on Multi-Layer Perceptron.
Comput. Informatics, 2025
2024
LLMEffiChecker: Understanding and Testing Efficiency Degradation of Large Language Models.
ACM Trans. Softw. Eng. Methodol., September, 2024
Deep palmprint recognition algorithm based on self-supervised learning and uncertainty loss.
Signal Image Video Process., July, 2024
Session-based recommendation with fusion of hypergraph item global and context features.
Knowl. Inf. Syst., May, 2024
Remote. Sens., January, 2024
PPM: Automated Generation of Diverse Programming Problems for Benchmarking Code Generation Models.
Proc. ACM Softw. Eng., 2024
2023
Character-to-Word Representation and Global Contextual Representation for Named Entity Recognition.
Neural Process. Lett., December, 2023
Comput. Speech Lang., 2023
2022
SN Comput. Sci., 2022
Automatic classification of thyroid nodules in ultrasound images using a multi-task attention network guided by clinical knowledge.
Comput. Biol. Medicine, 2022
2020
Feature selection by recursive binary gravitational search algorithm optimization for cancer classification.
Soft Comput., 2020
Unsupervised feature selection via graph matrix learning and the low-dimensional space learning for classification.
Eng. Appl. Artif. Intell., 2020
A new graph-preserving unsupervised feature selection embedding LLE with low-rank constraint and feature-level representation.
Artif. Intell. Rev., 2020