Ting Liu Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Researcher

University of Arkansas at Fayetteville

faculty

27 h-index 204 pubs 3,057 cited

Research Areas

Advanced Neural Network Applications Medical Imaging Techniques and Applications Radiomics and Machine Learning in Medical Imaging Deep Learning for Computer Vision Cardiovascular Function and Risk Factors Molecular Biology Techniques and Applications AI in cancer detection

Links

ORCID

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OverviewAI-generated summary

Ting Liu's research focuses on the application of deep learning techniques to complex computer vision and medical imaging problems. Liu has published work on developing novel neural network architectures, such as MALUNet, for precise skin lesion segmentation and exploring multi-source uncertainty mining for unsupervised saliency detection. Further research includes work on cross-modal meta-transfer for referring video object segmentation and adaptive co-teaching for unsupervised monocular depth estimation.

In addition to computer vision, Liu's research extends to areas of biomedical research, including investigating the molecular mechanisms underlying cardiovascular and liver cross-talk following myocardial infarction. Liu also investigates methods for learning from synthetic data for tasks like person re-identification, with publications exploring fine-grained attributes and rethinking illumination for improved generalization. Liu's scholarly output is substantial, with 204 total publications and an h-index of 27, indicating a significant contribution to their field.

Metrics

  • h-index: 27
  • Publications: 204
  • Citations: 3,057

Selected Publications

  • Machine learning-based identification of animal feeding operations in the United States on a parcel-scale (2025) DOI

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