Results 21 to 30 of about 222,333 (116)
Eng, 2023 This paper introduces a novel approach to leveraging features learned from both supervised and self-supervised paradigms, to improve image classification tasks, specifically for vehicle classification.
Shihan Ma, Jidong J. Yang
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SSBTCNet: Semi-Supervised Brain Tumor Classification Network
IEEE Access, 2023 Classification of brain tumors from the Magnetic Resonance Imaging (MRI) is a vital and challenging task for brain tumor diagnosis. Despite favorable results, from current Deep Learning (DL) methods used for the classification of brain tumors, the ...
Zubair Atha, Jyotismita Chaki
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Self-Supervised EEG Emotion Recognition Models Based on CNN
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 Emotion plays crucial roles in human life. Recently, emotion classification from electroencephalogram (EEG) signal has attracted attention by researchers due to the rapid development of brain computer interface (BCI) techniques and machine learning ...
Xingyi Wang +5 more
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Weakly supervised classification in high energy physics
Journal of High Energy Physics, 2017 As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations.
Lucio Mwinmaarong Dery +3 more
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Remote Sensing, 2022 Deep learning methods have become an integral part of computer vision and machine learning research by providing significant improvement performed in many tasks such as classification, regression, and detection. These gains have been also observed in the
Paul Berg, Minh-Tan Pham, Nicolas Courty
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Self-Supervised Learning for Solar Radio Spectrum Classification
Universe, 2022 Solar radio observation is an important way to study the Sun. Solar radio bursts contain important information about solar activity. Therefore, real-time automatic detection and classification of solar radio bursts are of great value for subsequent solar
Siqi Li +4 more
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Semi-Supervised DEGAN for Optical High-Resolution Remote Sensing Image Scene Classification
Remote Sensing, 2022 Semi-supervised methods have made remarkable achievements via utilizing unlabeled samples for optical high-resolution remote sensing scene classification.
Jia Li +4 more
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Remote Sensing, 2022 In recent years, supervised learning, represented by deep learning, has shown good performance in remote sensing image scene classification with its powerful feature learning ability. However, this method requires large-scale and high-quality handcrafted
Xiliang Chen, Guobin Zhu, Mingqing Liu
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Fine-Grained Classification of Hyperspectral Imagery Based on Deep Learning
Remote Sensing, 2019 Hyperspectral remote sensing obtains abundant spectral and spatial information of the observed object simultaneously. It is an opportunity to classify hyperspectral imagery (HSI) with a fine-grained manner.
Yushi Chen +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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