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   Articles with "pseudo label" as a keyword



Co‐training semi‐supervised medical image segmentation based on pseudo‐label weight balancing

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recommendations! Published in 2025 at "Medical Physics"

DOI: 10.1002/mp.17712

Abstract: Major challenges in current semi‐supervised segmentation methods: (1) The complementary nature of information in pseudo‐label: a key limitation of consistent regularization methods is the tendency of sub‐networks to converge to the consensus case early on,… read more here.

Keywords: segmentation; pseudo label; pseudo; semi supervised ... See more keywords

Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation

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recommendations! Published in 2021 at "International Journal of Computer Vision"

DOI: 10.1007/s11263-020-01395-y

Abstract: This paper focuses on the unsupervised domain adaptation of transferring the knowledge from the source domain to the target domain in the context of semantic segmentation. Existing approaches usually regard the pseudo label as the… read more here.

Keywords: pseudo label; semantic segmentation; domain; uncertainty ... See more keywords

Double-mix pseudo-label framework: enhancing semi-supervised segmentation on category-imbalanced CT volumes

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recommendations! Published in 2025 at "International Journal of Computer Assisted Radiology and Surgery"

DOI: 10.1007/s11548-024-03281-1

Abstract: Deep-learning-based supervised CT segmentation relies on fully and densely labeled data, the labeling process of which is time-consuming. In this study, our proposed method aims to improve segmentation performance on CT volumes with limited annotated… read more here.

Keywords: segmentation; pseudo label; double mix; supervised segmentation ... See more keywords

Pseudo-Label-Free Weakly Supervised Semantic Segmentation Using Image Masking

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3149587

Abstract: Weakly-supervised semantic segmentation (WSSS) aims to train a semantic segmentation network using weak labels. Recent approaches generate the pseudo-label from the image-level label and then exploit it as a pixel-level supervision in the segmentation network… read more here.

Keywords: network; weakly supervised; pseudo label; segmentation ... See more keywords

Alignment-Based Pseudo-Label Generation With Collaborative Filtering Mechanism for Enhanced Cross-Domain Aspect-Based Sentiment Analysis

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3469872

Abstract: Aspect-based sentiment analysis (ABSA) in areas such as online shopping and restaurants can effectively facilitate specific service improvements. However, ABSA performance heavily relies on high-quality labeled data, posing a major challenge in data-scarce domains. To… read more here.

Keywords: generation; pseudo label; pseudo; collaborative filtering ... See more keywords

Semi-Supervised Adaptive Pseudo-Label Feature Learning for Hyperspectral Image Classification in Internet of Things

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recommendations! Published in 2024 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2024.3412925

Abstract: Hyperspectral image (HSI) in Internet of Things (IoT) is a typical small sample data set, which is difficult and costly to label samples manually. In the feature extraction, it is difficult to increase the interclass… read more here.

Keywords: pseudo label; pseudo; label feature; internet things ... See more keywords

Domain Adaptation for Multilabel Remote Sensing Image Annotation With Contrastive Pseudo-Label Generation

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recommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2024.3490596

Abstract: Deep-learning-based multilabel remote sensing image annotation (MLRSIA) is receiving increasing attention in recent years. MLRSIA needs a large volume of labeled samples for effective training of the deep models. However, the scarcity of labeled samples… read more here.

Keywords: pseudo label; pseudo; remote sensing; annotation ... See more keywords

Graph Domain Adversarial Network With Dual-Weighted Pseudo-Label Loss for Hyperspectral Image Classification

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recommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2021.3135310

Abstract: A hyperspectral image (HSI) classification method named graph domain adversarial network with dual-weighted pseudo-label loss (GDAN-DWPL) is proposed in this letter. First, in order to extract more discriminative features, GDAN is applied to the transfer… read more here.

Keywords: label loss; pseudo label; weighted pseudo; dual weighted ... See more keywords

Prototype-Based Pseudo-Label Refinement for Semi-Supervised Hyperspectral Image Classification

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recommendations! Published in 2024 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2024.3385282

Abstract: Pseudo-label (PL) learning-based methods usually regard class confidence above a certain threshold for unlabeled samples as PLs, which may result in PLs still containing wrong labels. In this letter, we propose a prototype-based PL refinement… read more here.

Keywords: prototype based; hyperspectral image; pseudo label; semi supervised ... See more keywords

Pseudo Label Based on Multiple Clustering for Unsupervised Cross-Domain Person Re-Identification

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recommendations! Published in 2020 at "IEEE Signal Processing Letters"

DOI: 10.1109/lsp.2020.3016528

Abstract: Person re-identification (Re-ID) has achieved great improvement with the development of deep learning. However, domain adaptation in unsupervised Re-ID has always been a challenging task. Most existing works based on clustering only cluster once, which… read more here.

Keywords: person; pseudo label; person identification; multiple clustering ... See more keywords

Pseudo-Label-Vector-Guided Parallel Attention Network for Remaining Useful Life Prediction

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recommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"

DOI: 10.1109/tii.2022.3202832

Abstract: Prognostic health management (PHM) has become important in many industries as a critical technology to increase machine stability and operational efficiency. Recently, various methods using deep learning to estimate the remaining useful life (RUL) as… read more here.

Keywords: useful life; pseudo label; remaining useful; prediction ... See more keywords