Search Results - unsupervised clustering-labeling method

Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“… This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions…”
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Improving spherical k-means for document clustering: Fast initialization, sparse centroid projection, and efficient cluster labeling by Kim, Hyunjoong, Kim, Han Kyul, Cho, Sungzoon

“…•We provide unsupervised document cluster labeling method. Due to its simplicity and intuitive interpretability, spherical k-means is often used for clustering a large number of documents…”
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An Unsupervised Software Fault Prediction Approach Using Threshold Derivation by Kumar, Rakesh, Chaturvedi, Amrita, Kailasam, Lakshmanan

“…; hence, they demonstrate poor performance. To fill this gap, we develop an automated fault prediction approach, namely threshold clustering labeling/threshold clustering labeling plus (TCLP…”
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Spatial-Spectral Bipartite Graph Clustering With Low-Frequency Tensor Regularization for Hyperspectral and LiDAR Data by Cao, Zhe, Lu, Yihang, Xin, Haonan, Yu, Chuanqiang, Wang, Rong, Nie, Feiping

“… Unlike supervised methods requiring costly expert annotations, unsupervised clustering eliminates labeling needs, thereby offering an efficient solution for complex scene analysis with reduced deployment costs…”
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Deep radio signal clustering with interpretability analysis based on saliency map by Zhou, Huaji, Bai, Jing, Wang, Yiran, Ren, Junjie, Yang, Xiaoniu, Jiao, Licheng

“… Unsupervised radio signal clustering methods have recently become an urgent need for this situation…”
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FUSC: Fetal Ultrasound Semantic Clustering of Second-Trimester Scans Using Deep Self-Supervised Learning by Alasmawi, Hussain, Bricker, Leanne, Yaqub, Mohammad

“…The aim of this study was address the challenges posed by the manual labeling of fetal ultrasound images by introducing an unsupervised approach, the fetal ultrasound semantic clustering (FUSC) method…”
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LogGzip: Towards log Parsing with lossless compression by Gao, Donghui, Liu, Changjian, Chen, Ningjiang, Hu, Xiaochun

“… Supervised learning parsers require labor-intensive manual data labeling. Clustering-based parsers, as an unsupervised method, minimize expert involvement and manual annotation…”
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Convolutional Autoencoding and Gaussian Mixture Clustering for Unsupervised Beat-to-Beat Heart Rate Estimation of Electrocardiograms from Wearable Sensors by Zhong, Jun, Hai, Dong, Cheng, Jiaxin, Jiao, Changzhe, Gou, Shuiping, Liu, Yongfeng, Zhou, Hong, Zhu, Wenliang

“… Compared with the existing heartbeat classification/detection methods, the proposed unsupervised feature learning and heartbeat clustering method does not rely on accurate…”
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Motion Contrast Enhancement-based Crowd Motion Segmentation Method by Zhang, Xinfeng, Ni, Qili, Chen, Shuhan, Yang, Baoqing, Li, Bin

“… state.Supervised crowd motion segmentation methods require pixel-level training sets with high labeling costs, and thus unsupervised clustering methods are more promising for crowd motion…”
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An active learning approach for clustering single-cell RNA-seq data by Lin, Xiang, Liu, Haoran, Wei, Zhi, Roy, Senjuti Basu, Gao, Nan

“… Most methods for clustering scRNA-seq data use an unsupervised learning strategy. Since the clustering step is separated from the cell annotation and labeling step…”
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Unsupervised Classification in Hyperspectral Imagery With Nonlocal Total Variation and Primal-Dual Hybrid Gradient Algorithm by Wei Zhu, Chayes, Victoria, Tiard, Alexandre, Sanchez, Stephanie, Dahlberg, Devin, Bertozzi, Andrea L., Osher, Stanley, Zosso, Dominique, Da Kuang

“…). The variational problem is solved by the primal-dual hybrid gradient algorithm. By squaring the labeling function and using a stable simplex clustering routine, an unsupervised clustering method with random initialization can be implemented…”
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Discriminant non-stationary signal features’ clustering using hard and fuzzy cluster labeling by Ghoraani, Behnaz, Krishnan, Sridhar

“…, this article presents a novel direction to enhance the discriminatory power of pattern recognition methods…”
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Deep clustering of traffic signals using a single seismic station by Liu, Xinyu, Mi, Binbin, Xia, Jianghai, Zhou, Jie, Ma, Yulong

“… This deep clustering framework is unsupervised without manual labeling. Synthetic tests achieve a clustering accuracy of more than…”
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INTERNATIONAL PATENT: TECH UNIVERSITY OF KOREA INDUSTRY ACADEMIC COOPERATION FOUNDATION, 한국공학대학교산학협력단 FILES APPLICATION FOR "SELF-SUPERVISED AND UNSUPERVISED LEARNING-BASED IMAGE CLUSTERING ELECTRONIC DEVICE FOR AUTOMATED LABELING AND NOISE SAMPLING OF PCB SURFACE DEFECT IMAGE AND OPERATION METHOD THEREOF"

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An image processing and machine learning solution to automate Egyptian cotton lint grading by Fisher, Oliver J, Rady, Ahmed, El-Banna, Aly AA, Watson, Nicholas J, Emaish, Haitham H

“… While this method has been evaluated for classifying US and Chinese upland cotton staples, it has not been tested on Egyptian cotton, which has unique characteristics and grading requirements…”
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Hyperspectral Image Clustering Based on Unsupervised Broad Learning by Kong, Yi, Cheng, Yuhu, Chen, C. L. Philip, Wang, Xuesong

“…), unsupervised clustering methods have drawn great attention. The recently proposed broad learning (BL…”
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Automated labeling for unsupervised neural networks: a hierarchical approach by Tagliaferri, R., Capuano, N., Gargiulo, G.

“…In this paper a hybrid system and a hierarchical neural-net approaches are proposed to solve the automatic labeling problem for unsupervised clustering…”
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Image–text feature learning for unsupervised visible–infrared person re-identification by Guo, Jifeng, Pang, Zhiqi

“… To reduce labeling costs, unsupervised VI-ReID (UVI-ReID) methods typically use clustering algorithms to generate pseudo-labels and iteratively optimize the model based on these pseudo-labels…”
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Evaluation of single-cell RNAseq labelling algorithms using cancer datasets by Christensen, Erik, Luo, Ping, Turinsky, Andrei, Husić, Mia, Mahalanabis, Alaina, Naidas, Alaine, Diaz-Mejia, Juan Javier, Brudno, Michael, Pugh, Trevor, Ramani, Arun, Shooshtari, Parisa

“…Abstract Single-cell RNA sequencing (scRNA-seq) clustering and labelling methods are used to determine precise cellular composition of tissue samples…”
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Automated building typology clustering and identification using a variational autoencoder on digital land cadastres by de-Miguel-Rodriguez, Jaime, Requena-Garcia-Cruz, M.V., Romero-Sánchez, E., Morales-Esteban, A.

“…). Unlike traditional shape clustering approaches, that depend on predefined rules or manual labelling, the method employs unsupervised learning to identify building typologies, based solely…”
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