Results 31 to 40 of about 2,516,559 (186)
IEEE Access, 2018 Hyperspectral remote sensing sensors can provide plenty of valuable information with hundreds of spectral bands at each pixel. Feature selection and spectral-spatial information play an important role in the field of hyperspectral image (HSI ...
Lishuan Hu +3 more
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Unsupervised Feature Learning by Deep Sparse Coding [PDF]
, 2013 In this paper, we propose a new unsupervised feature learning framework, namely Deep Sparse Coding (DeepSC), that extends sparse coding to a multi-layer architecture for visual object recognition tasks.
He, Yunlong +4 more
core +2 more sources
Deep Learning Based Weighted Feature Fusion Approach for Sentiment Analysis
IEEE Access, 2019 Deep learning algorithms have achieved remarkable results in the natural language processing(NLP) and computer vision. Hence, a trend still going on to use these algorithms, such as convolution and recurrent neural networks, for text analytic task to ...
Mohd Usama +5 more
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Journal of Cybersecurity and Privacy, 2023 Session-replay bots are believed to be the latest and most sophisticated generation of web bots, and they are also very difficult to defend against. Combating session-replay bots is particularly challenging in online domains that are repeatedly visited ...
Shadi Sadeghpour, Natalija Vlajic
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Individualized Interaural Feature Learning and Personalized Binaural Localization Model
Applied Sciences, 2019 The increasing importance of spatial audio technologies has demonstrated the need and importance of correctly adapting to the individual characteristics of the human auditory system, and illustrates the crucial need for humanoid localization systems for ...
Xiang Wu +3 more
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Ants Learn Geometry and Features [PDF]
Current Biology, 2009 Rats trained to relocate a particular corner in a rectangular arena systematically confound the correct corner and the diametrically opposite one--this rotational error demonstrates the use of the geometry of space (i.e., the spatial arrangement of the different components of a visual scene).
Wystrach, Antoine, Beugnon, Guy
openaire +3 more sources
Multiview Deep Feature Learning Network for SAR Automatic Target Recognition
Remote Sensing, 2021 Multiview synthetic aperture radar (SAR) images contain much richer information for automatic target recognition (ATR) than a single-view one. It is desirable to establish a reasonable multiview ATR scheme and design effective ATR algorithm to thoroughly
Jifang Pei +6 more
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Feature Discovery by Competitive Learning* [PDF]
Cognitive Science, 1985 This paper reports the results of our studies with an unsupervised learning paradigm which we have called “Competitive Learning.” We have examined competitive learning using both computer simulation and formal analysis and have found that when it is applied to parallel networks of neuron‐like elements, many potentially useful learning tasks can be ...
D RUMELHART, D ZIPSER
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Constrained Deep Transfer Feature Learning and its Applications
, 2017 Feature learning with deep models has achieved impressive results for both data representation and classification for various vision tasks. Deep feature learning, however, typically requires a large amount of training data, which may not be feasible for ...
Ji, Qiang, Wu, Yue
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Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors
Sensors, 2018 Getting a good feature representation of data is paramount for Human Activity Recognition (HAR) using wearable sensors. An increasing number of feature learning approaches—in particular deep-learning based—have been proposed to extract an effective ...
Frédéric Li +4 more
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