Results 81 to 90 of about 637,915 (182)

A Multi-Label Image Classification Method based on Label Correlation Learning Network

Taiyuan Ligong Daxue xuebao
[Purposes] To meet the challenges posed by label feature confusions and limitations in label relationships in multi-label image classification tasks, a novel approach to multi-label image classification based on label correlation learning network (MLLCLN)
WANG Lufang, ZHANG Haiyun
doaj   +1 more source

A multi-label learning model for predicting drug-induced pathology in multi-organ based on toxicogenomics data. [PDF]

PLoS Comput Biol, 2022
Su R, Yang H, Wei L, Chen S, Zou Q.
europepmc   +1 more source

Improving accuracy for inferior alveolar nerve segmentation with multi-label of anatomical adjacent structures using active learning in cone-beam computed tomography

Scientific Reports
Recent advancements in deep learning have revolutionized digital dentistry, highlighting the importance of precise dental segmentation. This study leverages active learning with the three-dimensional (3D) nnU-net and multi-labels to improve segmentation ...
Sungchul On, Junhyeok Ock, Myungsoo Bae, Jae-Woo Park, Seung-Hak Baek, Sungwon Ham, Namkug Kim   +6 more
doaj   +1 more source

Multi-label Classification Based on Label-Aware Variational Autoencoder [PDF]

Jisuanji kexue yu tansuo
With the rise of the Internet, all kinds of data are growing rapidly, and how to utilize these sample data efficiently has become an important issue in the field of data mining.
SUN Hongjian, XU Pengyu, LIU Bing, JING Liping, YU Jian
doaj   +1 more source

MoRF-FUNCpred: Molecular Recognition Feature Function Prediction Based on Multi-Label Learning and Ensemble Learning. [PDF]

Front Pharmacol, 2022
Li H, Pang Y, Liu B, Yu L.
europepmc   +1 more source

Partial multi-label learning method based on deep forest

上海师范大学学报. 自然科学版
This paper proposes a biased multi label learning model based on deep forest architecture:the biased multi label deep forest (PMLDF) model, which combines the advantages of metric sensitive multi label deep forest and biased label forest, effectively ...
YUE Fan, QIU Feng
doaj   +1 more source

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion [PDF]

PeerJ Computer Science
In the realm of multi-label learning, instances are often characterized by a plurality of labels, diverging from the single-label paradigm prevalent in conventional datasets.
PKA Chitra, Saravana Balaji Balasubramanian, Omar Khattab, Mhd Omar Al-Kadri   +3 more
doaj   +2 more sources

Rapid Antibiotic Resistance Serial Prediction in Staphylococcus aureus Based on Large-Scale MALDI-TOF Data by Applying XGBoost in Multi-Label Learning. [PDF]

Front Microbiol, 2022
Zhang J, Wang Z, Wang HY, Chung CR, Horng JT, Lu JJ, Lee TY.   +6 more
europepmc   +1 more source

Metric Learning-Based Multi-Instance Multi-Label Classification With Label Correlation

IEEE Access, 2019
In multi-instance multi-label learning (MIML) problems, predicting the labels of unseen bags becomes difficult when the labels of their instances are not provided directly.
Haifeng Hu, Zhikai Cui, Jiansheng Wu, Kun Wang   +3 more
doaj   +1 more source

Nearest Labelset Using Double Distances for Multi-label Classification

, 2017
Multi-label classification is a type of supervised learning where an instance may belong to multiple labels simultaneously. Predicting each label independently has been criticized for not exploiting any correlation between labels.
Gweon, Hyukjun, Schonlau, Matthias, Steiner, Stefan   +2 more
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