Results 41 to 50 of about 3,113,449 (308)
Graph-based multi-label disease prediction model learning from medical data and domain knowledge
, 2022 In recent years, the means of disease diagnosis and treatment have been improved remarkably, along with the continuous development of technology and science. Researchers have spent tremendous time and effort to build models, with an aim to assist medical
Zhang, Ji +5 more
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A Semantic-Preserving Deep Hashing Model for Multi-Label Remote Sensing Image Retrieval
Remote Sensing, 2021 Conventional remote sensing image retrieval (RSIR) systems perform single-label retrieval with a single label to represent the most dominant semantic content for an image.
Qimin Cheng +5 more
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Weak Label Feature Selection Method Based on Neighborhood Rough Sets and Relief [PDF]
Jisuanji kexue, 2022 In multi-label learning and classification, existing feature selection algorithms based on neighborhood rough sets will use classification margin of samples as the neighborhood radius.However, when the margin is too large, the classification may be ...
SUN Lin, HUANG Miao-miao, XU Jiu-cheng
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Expede Herculem: Learning Multi Labels From Single Label
IEEE Access, 2018 Although there has been a lot of research in multi-label learning task, little attention has been paid on the weak label problem, in which only a subset of labels has been assigned to each instance in the training set.
Dejun Mu +5 more
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Big Data Mining and Analytics, 2020 Classifying wine according to their grade, price, and region of origin is a multi-label and multi-target problem in wineinformatics. Using wine reviews as the attributes, we compare several different multi-label/multi-target methods to the single-label ...
James Palmer +3 more
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RSVP performance optimisation using multi-objective evolutionary optimisation [PDF]
, 2005 The proposed uses of the resource reservation protocol (RSVP) now extend beyond reserving resources in Internet Protocol (IP) networks to being a generic signaling protocol for generalised multi-protocol label switching (GMPLS).
Sventek, J.S. +3 more
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Multi-label annotation of music [PDF]
2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR), 2015 Automatic annotation of an audio or a music piece with multiple labels helps in understanding the composition of a music. Such meta-level information can be very useful in applications such as music transcription, retrieval, organization and personalization.
Hiba Ahsan +2 more
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Multi-Label Inference for Crowdsourcing [PDF]
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018 When acquiring labels from crowdsourcing platforms, a task may be designed to include multiple labels and the values of each label may belong to a set of various distinct options, which is the so-called multi-class multi-label annotation. To improve the quality of labels, one task is independently completed by a group of heterogeneous crowdsourced ...
Jing Zhang 0015, Xindong Wu 0001
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Intelligent Neural Network Schemes for Multi-Class Classification
Applied Sciences, 2019 Multi-class classification is a very important technique in engineering applications, e.g., mechanical systems, mechanics and design innovations, applied materials in nanotechnologies, etc.
Ying-Jie You +3 more
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On the Stratification of Multi-label Data [PDF]
, 2011 Stratified sampling is a sampling method that takes into account the existence of disjoint groups within a population and produces samples where the proportion of these groups is maintained. In single-label classification tasks, groups are differentiated based on the value of the target variable.
Konstantinos Sechidis +2 more
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