Results 1 to 10 of about 1,715,429 (285)
MindReader: Unsupervised Classification of Electroencephalographic Data [PDF]
Sensors, 2023 Electroencephalogram (EEG) interpretation plays a critical role in the clinical assessment of neurological conditions, most notably epilepsy. However, EEG recordings are typically analyzed manually by highly specialized and heavily trained personnel ...
Salvador Daniel Rivas-Carrillo +6 more
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Unsupervised Classification of Quantum Data [PDF]
Physical Review X, 2019 We introduce the problem of unsupervised classification of quantum data, namely, of systems whose quantum states are unknown. We derive the optimal single-shot protocol for the binary case, where the states in a disordered input array are of two types ...
Gael Sentís +4 more
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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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Applied Sciences, 2021 The task of unsupervised anomalous sound detection (ASD) is challenging for detecting anomalous sounds from a large audio database without any annotated anomalous training data.
Yaoguang Wang +6 more
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Remote Sensing, 2022 Precise and accurate delineation of flooding areas with synthetic aperture radar (SAR) and multi-spectral (MS) data is challenging because flooded areas are inherently heterogeneous as emergent vegetation (EV) and turbid water (TW) are common.
Fatemeh Foroughnia +3 more
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Unsupervised classification of simulated magnetospheric regions [PDF]
Annales Geophysicae, 2021 In magnetospheric missions, burst-mode data sampling should be triggered in the presence of processes of scientific or operational interest. We present an unsupervised classification method for magnetospheric regions that could constitute the first step ...
M. E. Innocenti +5 more
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Unsupervised Domain Adaptation With Dense-Based Compaction for Hyperspectral Imagery
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Enormously hard work of label obtaining leads to the lack of enough annotated samples in the hyperspectral imagery (HSI). The mentioned reality inferred the unsupervised classification performance barely satisfactorily.
Chunyan Yu +4 more
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Research on Seismic Signal Analysis Based on Machine Learning
Applied Sciences, 2022 In this paper, the time series classification frontier method MiniRocket was used to classify earthquakes, blasts, and background noise. From supervised to unsupervised classification, a comprehensive analysis was carried out, and finally, the supervised
Xinxin Yin +6 more
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Contrastive Learning Based on Transformer for Hyperspectral Image Classification
Applied Sciences, 2021 Recently, deep learning has achieved breakthroughs in hyperspectral image (HSI) classification. Deep-learning-based classifiers require a large number of labeled samples for training to provide excellent performance.
Xiang Hu +4 more
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Land Cover Changes Based on Landsat Imagery Interpretation
Jurnal Teknik Pertanian Lampung, 2023 This paper presents the use of satellite data (i.e., Landsat-5 & Landsat-8) to interpret the change of land cover from 1997 to 2020. The study area covers the administrative boundary of Lumajang Regency.
Chairiyah Umi Rahayu +4 more
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