Peng Cao
20 papers · 2019–2026 · 10 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Gold π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (28) π£ Hot Topic Early Bird π Academic Marathon Β· Sprint
π€
Dynamic Duo
(13)
β‘
Prolific Year Β· Productive
π₯
Unstoppable Β· Bronze
π
Century Club Β· Bronze
π
Conference Pioneer
Venues
Top co-authors
Research topics
Machine Learning
(6)
Deep Learning
(5)
Learning Types Β· Machine Learning
(5)
Learning Types Β· Deep Learning
(4)
Healthcare & Medicine
(3)
Clinical
(3)
Core Methods
(3)
Computer Vision
(2)
Application Areas
(2)
Domain-Specific
(2)
Processing
(2)
Artificial Intelligence
(1)
Natural Language Processing
(1)
Analysis
(1)
Architectures
(1)
Keywords
medical image segmentation
(3)
contrastive learning
(2)
representation learning
(2)
domain generalization
(1)
model merging
(1)
transfer learning
(1)
multi-task learning
(1)
data augmentation
(1)
channel attention
(1)
pseudo labeling
(1)
deep regression
(1)
low-resource learning
(1)
supervised contrastive learning
(1)
feature distribution
(1)
semi-supervised learning
(1)
text style transfer
(1)
class imbalance
(1)
mutual information
(1)
label noise
(1)
semantic segmentation
(1)
Papers
Rethinking Depression Prediction from a Fine-Grained Subscore Modeling Perspective via Multi-Task Learning
ACL 2026
Style Content Decomposition-based Data Augmentation for Domain Generalizable Medical Image Segmentation
MIDL 2026
BrainPrompt: Domain Adaptation with Prompt Learning for Multi-site Brain Network Analysis
MICCAI 2025
ConStyX: Content Style Augmentation for Generalizable Medical Image Segmentation
MICCAI 2025
RIFNet: Bridging Modalities for Accurate and Detailed Ocular Disease Analysis
MICCAI 2025
Structure-aware MRI Translation: Multi-Modal Latent Diffusion Model with Arbitrary Missing Modalities
MICCAI 2025
3D-SAutoMed: Automatic Segment Anything Model for 3D Medical Image Segmentation from Local-Global Perspective
MICCAI 2024
A Clinical-oriented Lightweight Network for High-resolution Medical Image Enhancement
MICCAI 2024
A Clinical-oriented Multi-level Contrastive Learning Method for Disease Diagnosis in Low-quality Medical Images
MICCAI 2024
Exploring Spatio-Temporal Interpretable Dynamic Brain Function with Transformer for Brain Disorder Diagnosis
MICCAI 2024
Progressively Correcting Soft Labels via Teacher Team for Knowledge Distillation in Medical Image Segmentation
MICCAI 2024
Reusing Transferable Weight Increments for Low-resource Style Generation
EMNLP 2024
Self-Paced Sample Selection for Barely-Supervised Medical Image Segmentation
MICCAI 2024
Contactless Oxygen Monitoring with Radio Waves and Gated Transformer
MLHC 2023
Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
IJCAI 2023
Rank-N-Contrast: Learning Continuous Representations for Regression
NeurIPS 2023
Targeted Supervised Contrastive Learning for Long-Tailed Recognition
CVPR 2022
UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-Wise Perspective with Transformer
AAAI 2022
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning
ECCV 2020
L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise
NeurIPS 2019