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Shaohua Kevin Zhou

3 accepted papers

2026

Concept Bottleneck Models for Explainable Decision Making: A Survey of Progress, Taxonomy, and Future Directions

IJCAI 2026

Deep neural networks deliver strong performance but remain opaque, limiting their use in high-stakes domains that require transparency and human oversight. Concept Bottleneck Models (CBMs) address this gap by introducing a human-interpretable concept layer that mediates inputs and decisions, enablin

Cited by 0Scholar
2019

DuDoNet: Dual Domain Network for CT Metal Artifact Reduction

CVPR 2019poster

Computed tomography (CT) is an imaging modality widely used for medical diagnosis and treatment. CT images are often corrupted by undesirable artifacts when metallic implants are carried by patients, which creates the problem of metal artifact reduction (MAR). Existing methods for reducing the artif…

Cited by 267PDFScholar