Results 21 to 30 of about 2,740,047 (370)
Benchmark and application of unsupervised classification approaches for univariate data
Communications Physics, 2021 Unsupervised machine learning, and in particular data clustering, is a powerful approach for the analysis of datasets and identification of characteristic features occurring throughout a dataset. It is gaining popularity across scientific disciplines and
M. El Abbassi +5 more
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DLUT: Decoupled Learning-Based Unsupervised Tracker
Sensors, 2023 Unsupervised learning has shown immense potential in object tracking, where accurate classification and regression are crucial for unsupervised trackers.
Zhengjun Xu +4 more
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Adversarial Learning Approach to Unsupervised Labeling of Fine Art Paintings
IEEE Access, 2021 An automatic classification of fine art images is limited by the scarcity of high-quality labels made by art experts. This study aims to provide meaningful automatic labeling of fine art paintings (machine labeling) without the need for human annotation.
Catherine Sandoval +2 more
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Breast Image Classification Based on Multi-feature Joint Supervised Dictionary Learning [PDF]
Jisuanji gongcheng, 2018 Aiming at the problem that the unsupervised dictionary learning algorithm has low image classification accuracy,a supervised dictionary learning classification algorithm which combines with multiple image features is proposed.It uses the convolution ...
LIU Lihui,XU Jun,GONG Lei
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Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches [PDF]
International Conference on Natural Language Processing and Information Retrieval, 2022 Text classification of unseen classes is a challenging Natural Language Processing task and is mainly attempted using two different types of approaches. Similarity-based approaches attempt to classify instances based on similarities between text document
Tim Schopf, Daniel Braun, F. Matthes
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Unsupervised Classification by Iterative Voting
International Journal of Crowd Science, 2023 In the paper we present a simple algorithm for unsupervised classification of given items by a group of agents. The purpose of the algorithm is to provide fast and computationally light solutions of classification tasks by the randomly chosen agents. The
Evgeny Kagan, Alexander Novoselsky
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IEEE Transactions on Geoscience and Remote Sensing, 2022 Despite success in the same-scene hyperspectral image classification (HSIC), for the cross-scene classification, samples between source and target scenes are not drawn from the independent and identical distribution, resulting in significant performance ...
Chunhui Zhao +5 more
semanticscholar +1 more source
MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation [PDF]
Computer Vision and Pattern Recognition, 2021 For unsupervised domain adaptation (UDA), to alleviate the effect of domain shift, many approaches align the source and target domains in the feature space by adversarial learning or by explicitly aligning their statistics.
Guoqiang Wei +3 more
semanticscholar +1 more source
Interpretable and unsupervised phase classification
Physical Review Research, 2021 Fully automated classification methods that provide direct physical insights into phase diagrams are of current interest. Interpretable, i.e., fully explainable, methods are desired for which we understand why they yield a given phase classification ...
Julian Arnold +3 more
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Self-supervised Regularization for Text Classification
Transactions of the Association for Computational Linguistics, 2021 Text classification is a widely studied problem and has broad applications. In many real-world problems, the number of texts for training classification models is limited, which renders these models prone to overfitting.
Meng Zhou, Zechen Li, Pengtao Xie
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