Results 51 to 60 of about 259,134 (247)
Semi-supervised Remote Sensing Image Scene Classification Based on Generative Adversarial Networks
International Journal of Computational Intelligence Systems, 2022 With the availability of numerous high-resolution remote sensing images, remote sensing image scene classification has been widely used in various fields. Compared with the field of natural images, the insufficient number of labeled remote sensing images
Dongen Guo +3 more
doaj +1 more source
HSSDA: Hierarchical relation aided Semi-Supervised Domain Adaptation
AI Open, 2022 The mainstream domain adaptation (DA) methods transfer the supervised source domain knowledge to the unsupervised or semi-supervised target domain, so as to assist the classification task in the target domain.
Xiechao Guo, Ruiping Liu, Dandan Song
doaj +1 more source
Minimum Density Hyperplanes [PDF]
, 2016 Associating distinct groups of objects (clusters) with contiguous regions of high probability density (high-density clusters), is central to many statistical and machine learning approaches to the classification of unlabelled data.
Hofmeyr, David P. +2 more
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Weakly-Supervised Neural Text Classification
, 2018 Deep neural networks are gaining increasing popularity for the classic text classification task, due to their strong expressive power and less requirement for feature engineering. Despite such attractiveness, neural text classification models suffer from
Han, Jiawei +3 more
core +1 more source
Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Fingerprint Liveness Detection in the Presence of Capable Intruders
Sensors, 2015 Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the
Ana F. Sequeira, Jaime S. Cardoso
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LP-MLTSVM: Laplacian Multi-Label Twin Support Vector Machine for Semi-Supervised Classification
IEEE Access, 2022 In the machine learning jargon, multi-label classification refers to a task where multiple mutually non-exclusive class labels are assigned to a single instance. Generally, the lack of sufficient labeled training data demanded by a classification task is
Farhad Gharebaghi, Ali Amiri
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective This study aims to identify both fluid and neuroimaging biomarkers for CSF1R‐RD that can inform the optimal timing of treatment administration to maximize therapeutic benefit, while also providing sensitive quantitative measurements to monitor disease progression.
Tomasz Chmiela +13 more
wiley +1 more source
Consistency Self-Training Semi-Supervised Method for Road Extraction from Remote Sensing Images
Remote SensingRoad extraction techniques based on remote sensing image have significantly advanced. Currently, fully supervised road segmentation neural networks based on remote sensing images require a significant number of densely labeled road samples, limiting ...
Xingjian Gu +4 more
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Towards Semi-Supervised Universal Graph Classification
IEEE Transactions on Knowledge and Data EngineeringAccepted by IEEE Transactions on Knowledge and Data Engineering (TKDE 2023)
Xiao Luo +4 more
openaire +2 more sources