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Pseudo Label
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A lightweight but very power technique for semi supervised learning
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation
FedGSCA: Medical Federated Learning with Global Sample Selector and Client Adaptive Adjuster under Label Noise
Leveraging Out-of-Distribution Unlabeled Images: Semi-Supervised Semantic Segmentation with an Open-Vocabulary Model
QUEST: Quality-aware Semi-supervised Table Extraction for Business Documents
Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languages
Robust Unsupervised Adaptation of a Speech Recogniser Using Entropy Minimisation and Speaker Codes
SRPL-SFDA: SAM-Guided Reliable Pseudo-Labels for Source-Free Domain Adaptation in Medical Image Segmentation
Segment Concealed Objects with Incomplete Supervision
MultiMatch: Multihead Consistency Regularization Matching for Semi-Supervised Text Classification
Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models
L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
Shuffle PatchMix Augmentation with Confidence-Margin Weighted Pseudo-Labels for Enhanced Source-Free Domain Adaptation
D2AF: A Dual-Driven Annotation and Filtering Framework for Visual Grounding
CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation
Collaborative Learning for Unsupervised Multimodal Remote Sensing Image Registration: Integrating Self-Supervision and MIM-Guided Diffusion-Based Image Translation
RefAV: Towards Planning-Centric Scenario Mining
Semi-Supervised Conformal Prediction With Unlabeled Nonconformity Score
Certainty and Uncertainty Guided Active Domain Adaptation
A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
ViaRL: Adaptive Temporal Grounding via Visual Iterated Amplification Reinforcement Learning
Mutual Evidential Deep Learning for Medical Image Segmentation
Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation
TransPL: VQ-Code Transition Matrices for Pseudo-Labeling of Time Series Unsupervised Domain Adaptation
Using Foundation Models as Pseudo-Label Generators for Pre-Clinical 4D Cardiac CT Segmentation
Robust Emotion Recognition via Bi-Level Self-Supervised Continual Learning
Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation
Building-Guided Pseudo-Label Learning for Cross-Modal Building Damage Mapping
3D Can Be Explored In 2D: Pseudo-Label Generation for LiDAR Point Clouds Using Sensor-Intensity-Based 2D Semantic Segmentation
Modality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T Tracking
Robust Duality Learning for Unsupervised Visible-Infrared Person Re-Identification
High-Fidelity Pseudo-label Generation by Large Language Models for Training Robust Radiology Report Classifiers
Consistency-aware Fake Videos Detection on Short Video Platforms
OpenAVS: Training-Free Open-Vocabulary Audio Visual Segmentation with Foundational Models
Semantic-Aligned Learning with Collaborative Refinement for Unsupervised VI-ReID
Unsupervised Cross-Domain 3D Human Pose Estimation via Pseudo-Label-Guided Global Transforms
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