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检索条件"主题词=Multi-instance Multi-label Learning"
57 条 记 录,以下是1-10 订阅
排序:
Abductive multi-instance multi-label learning for periodontal disease classification with prior domain knowledge
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MEDICAL IMAGE ANALYSIS 2025年 101卷 103452页
作者: Wu, Zi-Yuan Guo, Wei Zhou, Wei Ye, Han-Jia Jiang, Yuan Li, Houxuan Zhou, Zhi-Hua Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210023 Peoples R China Nanjing Univ Sch Artificial Intelligence Nanjing 210023 Peoples R China Nanjing Univ Affiliated Hosp Nanjing Stomatol Hosp Med SchRes Inst Stomatol Nanjing 210008 Peoples R China
Machine learning is widely used in dentistry nowadays, offering efficient solutions for diagnosing dental diseases, such as periodontitis and gingivitis. Most existing methods for diagnosing periodontal diseases follo... 详细信息
来源: 评论
Imbalanced multi-instance multi-label learning via tensor product-based semantic fusion
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FRONTIERS OF COMPUTER SCIENCE 2025年 第8期19卷 1-12页
作者: Zhang, Xinyue Luo, Tingjin Natl Univ Def Technol Coll Sci Changsha 410073 Peoples R China
With powerful expressiveness of multi-instance multi-label learning (MIML) for objects with multiple semantics and its great flexibility for complex object structures, MIML has been widely applied to various applicati... 详细信息
来源: 评论
multi-instance multi-label learning Based on Parallel Attention and Local label Manifold Correlation  9
Multi-instance Multi-label Learning Based on Parallel Attent...
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9th IEEE International Conference on Data Science and Advanced Analytics (DSAA)
作者: Yang, Mei Tang, Wen-Tao Min, Fan Southwest Petr Univ Sch Comp Sci Chengdu Peoples R China Southwest Petr Univ Sch Comp Sci Inst Artificial Intelligence Chengdu Peoples R China
Real-world applications always contain complex data objects with multiple semantics. The machine learning tasks generalized from these applications can be formulated as multiinstance multi-label learning (MIML) proble... 详细信息
来源: 评论
MIML-GAN: A GAN-Based Algorithm for multi-instance multi-label learning on Overlapping Signal Waveform Recognition
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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2023年 71卷 859-872页
作者: Pan, Zesi Wang, Bo Zhang, Ruibin Wang, Shafei Li, Yunjie Li, Yan Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China Univ Int Business & Econ Sch Informat Technol & Management Beijing 100029 Peoples R China Beijing Inst Technol Sch Cyberspace Sci & Technol Beijing 100081 Peoples R China
Existing studies for automatic waveform recognition of overlapping signals have mostly been conducted in a supervised manner. Although demonstrating superior performance in recent years, supervised methods rely heavil... 详细信息
来源: 评论
Hierarchical multi-instance multi-label learning for Chinese patent text classification
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CONNECTION SCIENCE 2024年 第1期36卷
作者: Liu, Yunduo Xu, Fang Zhao, Yushan Ma, Zichen Wang, Tengke Zhang, Shunxiang Tian, Yuhao Anhui Univ Sci & Technol Sch Comp Sci & Engn Huainan Peoples R China Hefei Comprehens Natl Sci Ctr Inst Artificial Intelligence Hefei Peoples R China Anhui Univ Sci & Technol Sch Foreign Languages Huainan Peoples R China Anhui Univ Sci & Technol Sch Math & Big Data Huainan Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau Peoples R China
To further enhance the accuracy of the Chinese patent classification, this paper proposes a model, based on the patent structure and takes the patent claim as subjects, with multi-instance multi-label learning as the ... 详细信息
来源: 评论
Predicting the function of rice proteins through multi-instance multi-label learning based on multiple features fusion
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BRIEFINGS IN BIOINFORMATICS 2022年 第3期23卷 bbac095-bbac095页
作者: Liu, Jing Tang, Xinghua Cui, Shuanglong Guan, Xiao Shanghai Maritime Univ Informat Engn Coll Shanghai 201306 Peoples R China Univ Shanghai Sci & Technol Sch Hlth Sci & Engn Shanghai 200093 Peoples R China
There are a large number of unannotated proteins with unknown functions in rice, which are difficult to be verified by biological experiments. Therefore, computational method is one of the mainstream methods for rice ... 详细信息
来源: 评论
Automatic Waveform Recognition of Overlapping LPI Radar Signals Based on multi-instance multi-label learning
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IEEE SIGNAL PROCESSING LETTERS 2020年 27卷 1275-1279页
作者: Pan, Zesi Wang, Shafei Zhu, Mengtao Li, Yunjie Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Northern Inst Elect Equipment Beijing 100091 Peoples R China Peng Cheng Lab Shenzhen 518055 Peoples R China
In an ever-increasingly complex electromagnetic environment, multiple low probability of intercept (LPI) radar emitters may transmit their own signals simultaneously on similar bands, resulting in overlapping receivin... 详细信息
来源: 评论
Fast multi-instance multi-label learning
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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2019年 第11期41卷 2614-2627页
作者: Huang, Sheng-Jun Gao, Wei Zhou, Zhi-Hua Nanjing Univ Natl Key Lab Novel Software Technol Nanjing 210023 Jiangsu Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Jiangsu Peoples R China
In many real-world tasks, particularly those involving data objects with complicated semantics such as images and texts, one object can be represented by multiple instances and simultaneously be associated with multip... 详细信息
来源: 评论
DEEP FEATURE REPRESENTATIONS AND multi-instance multi-label learning OF WHOLE SLIDE BREAST HISTOPATHOLOGY IMAGES
DEEP FEATURE REPRESENTATIONS AND MULTI-INSTANCE MULTI-LABEL ...
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作者: Caner Mercan Bilkent University
学位级别:博士
The examination of a tissue sample has traditionally involved a pathologist investigating the case under a microscope. Whole slide imaging technology has recently been utilized for the digitization of biopsy slides, r... 详细信息
来源: 评论
An improved multi-instance multi-label learning algorithm based on representative instances selection and label correlations
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INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING 2018年 第3期9卷 268-277页
作者: Liu, Chanjuan Chen, Tongtong Zou, Hailin Ding, Xinmiao Wang, Yuling Ludong Univ Sch Informat & Elect Engn Prov Key Lab Cyber Phys Syst & Intelligent Contro Yantai 264025 Peoples R China Shandong Inst Business & Technol Sch Informat & Elect Engn Yantai 264005 Peoples R China Shandong Jianzhu Univ Dept Informat & Elect Engn Jinan 250101 Shandong Peoples R China
multi-instance multi-label learning (MIML) has been successfully used in image and text classification problems. It is noteworthy that few of the previous studies consider the pattern-label relations. Inevitably, ther... 详细信息
来源: 评论