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Pseudo Label

A lightweight but very power technique for semi supervised learning

Papers

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Showing 551–575 of 956 papers

TitleStatusHype
Uncertainty-Guided Never-Ending Learning to Drive—0
Data-Free Quantization via Pseudo-label Filtering—0
PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process GuidanceCode0
SSFlowNet: Semi-supervised Scene Flow Estimation On Point Clouds With Pseudo Label—0
Pixel-Level Change Detection Pseudo-Label Learning for Remote Sensing Change CaptioningCode0
Federated Continual Novel Class Learning—0
Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI—0
Pixel-Superpixel Contrastive Learning and Pseudo-Label Correction for Hyperspectral Image Clustering—0
Student as an Inherent Denoiser of Noisy Teacher—0
Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization—0
Semi-supervised Active Learning for Video Action DetectionCode0
Taking it further: leveraging pseudo labels for field delineation across label-scarce smallholder regions—0
Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions—0
RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Inter-label Correlations—0
Learning Part Segmentation from Synthetic Animals—0
Turn Down the Noise: Leveraging Diffusion Models for Test-time Adaptation via Pseudo-label Ensembling—0
Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs—0
Pseudo-label Correction for Instance-dependent Noise Using Teacher-student Framework—0
Density-Guided Dense Pseudo Label Selection For Semi-supervised Oriented Object DetectionCode0
Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image SegmentationCode0
SSASS: Semi-Supervised Approach for Stenosis Segmentation—0
SCADI: Self-supervised Causal Disentanglement in Latent Variable ModelsCode0
FireMatch: A Semi-Supervised Video Fire Detection Network Based on Consistency and Distribution Alignment—0
Generating Unbiased Pseudo-labels via a Theoretically Guaranteed Chebyshev Constraint to Unify Semi-supervised Classification and RegressionCode0
Towards Generalized Multi-stage Clustering: Multi-view Self-distillation—0
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