Behzad Bozorgtabar
20 papers · 2019–2026 · 6 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (36) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🧭
Keyword Pioneer
🧬
Topic Evolution
🤝
Dynamic Duo
(15)
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
🗃️
Keyword Collector
(94)
⚡
Prolific Year · Productive
Top co-authors
Research topics
Machine Learning
(16)
Computer Vision
(13)
Deep Learning
(13)
Learning Types · Machine Learning
(11)
Domain-Specific
(8)
Healthcare & Medicine
(7)
Application Areas
(7)
Clinical
(7)
Artificial Intelligence
(6)
Models
(6)
Learning Types · Deep Learning
(5)
Core Methods
(4)
Processing
(4)
Analysis
(3)
Architectures
(3)
Keywords
self-supervised learning
(7)
data augmentation
(4)
domain shift
(4)
medical imaging
(4)
semantic segmentation
(3)
domain adaptation
(3)
medical image segmentation
(3)
anomaly detection
(2)
image restoration
(2)
active learning
(2)
nearest neighbor
(2)
test-time adaptation
(2)
online clustering
(1)
contrastive learning
(1)
domain generalization
(1)
conformal prediction
(1)
representation learning
(1)
object detection
(1)
feature learning
(1)
uncertainty quantification
(1)
Papers
LATA: Laplacian-Assisted Transductive Adaptation for Conformal Uncertainty in Medical VLMs
CVPR 2026
VALIANT: Prompt Instability for Active Learning in Black-Box Medical Imaging
AAAI 2026
A Simple Framework for Open-Vocabulary Zero-Shot Segmentation
ICLR 2025
Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet
WACV 2025
Combining Graph Transformers Based Multi-Label Active Learning and Informative Data Augmentation for Chest Xray Classification
AAAI 2024
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
ICLR 2024
Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation
ICLR 2024
Adaptive Similarity Bootstrapping for Self-Distillation Based Representation Learning
ICCV 2023
Attention-Conditioned Augmentations for Self-Supervised Anomaly Detection and Localization
AAAI 2023
CrOC: Cross-View Online Clustering for Dense Visual Representation Learning
CVPR 2023
ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification
WACV 2023
TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation
CVPR 2023
OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift
MIDL 2022
Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation
WACV 2022
Benefiting From Bicubically Down-Sampled Images for Learning Real-World Image Super-Resolution
WACV 2021
Quantifying Explainers of Graph Neural Networks in Computational Pathology
CVPR 2021
Self-Rule to Adapt: Learning Generalized Features from Sparsely-Labeled Data Using Unsupervised Domain Adaptation for Colorectal Cancer Tissue Phenotyping
MIDL 2021
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation
CVPR 2020
SROBB: Targeted Perceptual Loss for Single Image Super-Resolution
ICCV 2019
SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion
ICCV 2019