Results 1 to 10 of about 12,744 (261)
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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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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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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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 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 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 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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Weakly Supervised Correspondence Learning
2022 International Conference on Robotics and Automation (ICRA), 2022 Correspondence learning is a fundamental problem in robotics, which aims to learn a mapping between state, action pairs of agents of different dynamics or embodiments. However, current correspondence learning methods either leverage strictly paired data -- which are often difficult to collect -- or learn in an unsupervised fashion from unpaired data ...
Zihan Wang +3 more
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Semi-Supervised Learning Matting Algorithm Based on Semantic Consistency of Trimaps
Applied Sciences, 2023 Image matting methods based on deep learning have made tremendous success. However, the success of previous image matting methods typically relies on a massive amount of pixel-level labeled data, which are time-consuming and costly to obtain.
Yating Kong +3 more
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