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Weakly supervised machine learning
CAAI Transactions on Intelligence Technology, 2023 Supervised learning aims to build a function or model that seeks as many mappings as possible between the training data and outputs, where each training data will predict as a label to match its corresponding ground‐truth value.
Zeyu Ren, Shuihua Wang, Yudong Zhang
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Sensors, 2022 The total boll count from a plant is one of the most important phenotypic traits for cotton breeding and is also an important factor for growers to estimate the final yield.
Shrinidhi Adke +3 more
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Weakly supervised label learning flows
Neural NetworksAccepted as a full length research article by Neural ...
Wenzhuo Song, You Lu, Bert Huang
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Weakly supervised foreground learning for weakly supervised localization and detection
Pattern Recognition, 2023 Modern deep learning models require large amounts of accurately annotated data, which is often difficult to satisfy. Hence, weakly supervised tasks, including weakly supervised object localization~(WSOL) and detection~(WSOD), have recently received attention in the computer vision community.
Jianxin Wu, Chen-Lin Zhang, Yin Li
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A Semi-Automatic Magnetic Resonance Imaging Annotation Algorithm Based on Semi-Weakly Supervised Learning [PDF]
SensorsThe annotation of magnetic resonance imaging (MRI) images plays an important role in deep learning-based MRI segmentation tasks. Semi-automatic annotation algorithms are helpful for improving the efficiency and reducing the difficulty of MRI image ...
Shaolong Chen, Zhiyong Zhang
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Weakly Supervised Learning Approach for Implicit Aspect Extraction
Information, 2023 Aspect-based sentiment analysis (ABSA) is a process to extract an aspect of a product from a customer review and identify its polarity. Most previous studies of ABSA focused on explicit aspects, but implicit aspects have not yet been the subject of much ...
Aye Aye Mar +2 more
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Weakly supervised learning for classification of lung cytological images using attention-based multiple instance learning [PDF]
Scientific Reports, 2021 In cytological examination, suspicious cells are evaluated regarding malignancy and cancer type. To assist this, we previously proposed an automated method based on supervised learning that classifies cells in lung cytological images as benign or ...
Atsushi Teramoto +7 more
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SentiUrdu-1M: A large-scale tweet dataset for Urdu text sentiment analysis using weakly supervised learning [PDF]
PLoS ONE, 2023 Low-resource languages are gaining much-needed attention with the advent of deep learning models and pre-trained word embedding. Though spoken by more than 230 million people worldwide, Urdu is one such low-resource language that has recently gained ...
Abdul Ghafoor +5 more
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Weakly Supervised Contrastive Learning [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Unsupervised visual representation learning has gained much attention from the computer vision community because of the recent achievement of contrastive learning. Most of the existing contrastive learning frameworks adopt the instance discrimination as the pretext task, which treating every single instance as a different class.
Mingkai Zheng +6 more
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Safe Weakly Supervised Learning [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 Weakly supervised learning (WSL) refers to learning from a large amount of weak supervision data. This includes i) incomplete supervision (e.g., semi-supervised learning); ii) inexact supervision (e.g., multi-instance learning) and iii) inaccurate supervision (e.g., label noise learning). Unlike supervised learning which typically achieves performance
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