Results 21 to 30 of about 1,256,985 (257)
IEEE Access, 2019 Multi-label learning deals with problems in which each instance is associated with a set of labels. Most multi-label learning algorithms ignore the potential distribution differences between the training domain and the test domain in the instance space ...
Siyu Jiang +6 more
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An improved multi-object instance segmentation based on deep learning
Kuwait Journal of Science, 2022 Given the recent breakthroughs in recent years, Deep learning (DL) networks have attracted growing interest and attention by researchers and scholars alike due to its importance in detecting and instance segmentation of objects in an image.
Nawaf Alshdaifat +2 more
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Multi-instance multi-label learning
Artificial Intelligence, 2012 64 pages, 10 figures; Artificial Intelligence ...
Zhou, Zhi-Hua +3 more
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Query-Driven Multi-Instance Learning
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 We introduce a query-driven approach (qMIL) to multi-instance learning where the queries aim to uncover the class labels embodied in a given bag of instances. Specifically, it solves a multi-instance multi-label learning (MIML) problem with a more challenging setting than the conventional one.
Yen-Chi Hsu +3 more
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IET Computer Vision, 2018 The classification of natural scene images is multi‐instance multi‐label (MIML) for many labels that exist in a natural scene image. The traditional method of solving MIML is to degenerate it into single‐instance single‐label learning (SISL).
Hu Zhang, Wei Wu, Ding Wang
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Face Gender and Age Classification Based on Multi-Task, Multi-Instance and Multi-Scale Learning
Applied Sciences, 2022 Automated facial gender and age classification has remained a challenge because of the high inter-subject and intra-subject variations. We addressed this challenging problem by studying multi-instance- and multi-scale-enhanced multi-task random forest ...
Haibin Liao +5 more
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A multi-instance multi-label improved algorithm based on semi-supervised learning
Dianzi Jishu Yingyong, 2019 The multi-instance multi-label learning framework is a new machine learning framework for solving ambiguity problems. In the multi-instance multi-label learning framework, an object is represented by a set of examples and is associated with a set of ...
Li Cunhe, Zhang Zhenkai, Zhu Hongbo
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Optimal Representative Distribution Margin Machine for Multi-Instance Learning
IEEE Access, 2020 Multi-instance learning (MIL) plays an important role in many real applications, such as image recognition and text classification. The instance-based approach selects instances in each bag to train and has drawn significant attention recently.
Tianxiang Luan +3 more
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Instance structure based multi-label learning with missing labels
Tongxin xuebao, 2021 To address the problem that the existing methods in multi-label learning did not efficiently deal with the problems, the instance structure based multi-label learning scheme with missing labels was proposed.By considering the feature and label structure ...
Tianzhu CHEN +3 more
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Large-Scale Multi-Label Learning with Incomplete Label Assignments [PDF]
, 2014 Multi-label learning deals with the classification problems where each instance can be assigned with multiple labels simultaneously. Conventional multi-label learning approaches mainly focus on exploiting label correlations.
Fan, Wei +6 more
core +2 more sources