Suchergebnisse - multi-supervised algorithm

Multi-branch global Transformer‐assisted network for fault diagnosis von Shao, Xiaorui, Kim, Chang-Soo

“… Fault Diagnosis (FD) is critical in smart manufacturing, enabling predictive maintenance, reducing operational costs, and enhancing system reliability. To deal …”
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A multi-instance multi-label improved algorithm based on semi-supervised learning von Li Cunhe, Zhang Zhenkai, Zhu Hongbo

“… + algorithm is a classical classification algorithm that uses degenerate ideas in the multi-instance multi-label learning framework. It can …”
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DREAM2 Challenge: Integrated Multi‐Array Supervised Learning Algorithm for BCL6 Transcriptional Targets Prediction von Lee, W.H., Narang, V., Xu, H., Lin, F., Chin, K.C., Sung, W.K.

“… In the Dialogue for Reverse Engineering Assessments and Methods Conference (DREAM2) BCL6 target identification challenge, we were given a list of 200 genes and …”
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Cross-Domain Recommendation Algorithm Combining Multi-personalized Bridges and Self-supervised Learning von WANG Yonggui, LIU Danni

“… A cross-domain recommendation algorithm combining multi-personalized bridges and self-supervised learning (MS-PTUPCDR …”
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Corrections to "Self-Supervised Adaptive Learning Algorithm for Multi-Horizon Electricity Price Forecasting" von Zamee, Muhammad Ahsan, Lee, Yeongsang, Won, Dongjun

“… Presents corrections to the paper, Corrections to "Self-Supervised Adaptive Learning Algorithm for Multi-Horizon Electricity Price Forecasting" …”
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Multi-Supervised Feature Fusion Attention Network for Clouds and Shadows Detection von Ji, Huiwen, Xia, Min, Zhang, Dongsheng, Lin, Haifeng

“… Based on the visual and distribution characteristics of clouds and their shadows in remote sensing imagery, this paper provides a multi-supervised feature fusion attention network …”
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MSC-CSMC: A multi-objective semi-supervised clustering algorithm based on constraints selection and multi-source constraints for gene expression data von Wang, Zeyuan, Gu, Hong, Zhao, Minghui, Li, Dan, Wang, Jia

“… To this end, the research proposes a new multi-objective semi-supervised clustering algorithm based on constraints selection and multi-source constraints (MSC-CSMC …”
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Weakly supervised semantic segmentation and optimization algorithm based on multi-scale feature model von Changzhen XIONG, Hui ZHI

“… In order to improve the accuracy of weakly-supervised semantic segmentation method,a segmentation and optimization algorithm that combines multi-scale feature …”
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Weakly supervised semantic segmentation and optimization algorithm based on multi-scale feature model von Changzhen XIONG, Hui ZHI

“… In order to improve the accuracy of weakly-supervised semantic segmentation method,a segmentation and optimization algorithm that combines multi-scale feature …”
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A supervised multi-spike learning algorithm based on gradient descent for spiking neural networks von Xu, Yan, Zeng, Xiaoqin, Han, Lixin, Yang, Jing

“… We use a supervised multi-spike learning algorithm for spiking neural networks (SNNs) with temporal encoding to simulate the learning mechanism of biological neurons in which the SNN output spike trains are encoded by firing times …”
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The stochastic multi-gradient algorithm for multi-objective optimization and its application to supervised machine learning von Liu, S., Vicente, L. N.

“… Optimization of conflicting functions is of paramount importance in decision making, and real world applications frequently involve data that is uncertain or …”
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ISSMLCF: an inductive semi-supervised multi-label learning algorithm with co-forest paradigm von Liu, Wenhao, Duan, Jicong, Shao, Changbin, Yang, Xibei, Xu, Sen, Yu, Hualong

“… leverage between the quality of predictive models and labeling costs. In this study, a novel semi-supervised multi-label learning algorithm called the inductive semi-supervised multi-label learning algorithm based on co-forest paradigm (ISSMLCF) was proposed …”
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A semi-supervised learning algorithm for multi-label classification and multi-assignment clustering problems based on a Multivariate Data Analysis von Gull, Carlos Quintero, Aguilar, Jose

“… On the other hand, we are starting to see machine learning algorithms that solve the problem of multi-label classification and multiple cluster assignment, but there are no algorithms that solve …”
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A resource limited artificial immune system algorithm for supervised classification of multi/hyper-spectral remote sensing imagery von Zhang, L., Zhong, Y., Huang, B., Li, P.

“… This paper explores a novel artificial immune algorithm based on the resource limited principles for supervised multi/hyper-spectral image classification …”
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Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm von Maximov, Yury, Amini, Massih-Reza, Harchaoui, Zaid

“… We propose Rademacher complexity bounds for multi-class classifiers trained with a two-step semi-supervised model …”
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Active Semi-Supervised Clustering Algorithm for Multi-Density Datasets von Atwa, Walid, Almazroi, Abdulwahab Ali, Aldhahr, Eman A., Janbi, Nourah Fahad

“… This research proposes an active semi-supervised density-based clustering algorithm, termed "ASS-DBSCAN," designed specifically for clustering multi-density data …”
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MGFKD: A semi-supervised multi-source domain adaptation algorithm for cross-subject EEG emotion recognition von Zhang, Rui, Guo, Huifeng, Xu, Zongxin, Hu, Yuxia, Chen, Mingming, Zhang, Lipeng

“… To solve this problem, this paper proposes a semi-supervised domain adaptive algorithm based on few labeled samples of target subject, which called multi-domain geodesic flow kernel dynamic distribution alignment (MGFKD …”
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Multi-Modal Self-Supervised Learning Algorithm-Based Product Recommendation von Gao, Li, Fan, Haiping, Chen, Qingkui, Yang, Heyu

“… For this reason, this paper proposes Multi-Modal Self-Supervised Learning Algorithm Based Product Recommendation (MMSLRec). 1 …”
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Survey of Multi-label Classification Based on Supervised and Semi-supervised Learning von Wu, Hong-xin, Han, Meng, Chen, Zhi-qiang, Zhang, Xi-long, Li, Mu-hang

“… Most of the traditional multi-label classification algorithms use supervised learning, but in real life, there are many unlabeled …”
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Research on semi-supervised multi-graph classification algorithm based on MR-MGSSL for sensor network von Gang, Yang, Na, Zhang, Tao, Jin, Dawei, Wang, Yinzhu, Kang, Feng, Gao

“… Therefore, this paper proposes an MR-MGSSL algorithm and applies it to the classification of semi-supervised multi-graph …”
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