Results 41 to 50 of about 2,516,559 (186)
Applied Sciences, 2022 Speech emotion recognition (SER), a rapidly evolving task that aims to recognize the emotion of speakers, has become a key research area in affective computing.
Yiping Ma, Wei Wang
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Feature learning in feature-sample networks using multi-objective optimization
, 2017 Data and knowledge representation are fundamental concepts in machine learning. The quality of the representation impacts the performance of the learning model directly.
Tinós, Renato +2 more
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Sensors, 2022 In the last decades, data-driven methods have gained great popularity in the industry, supported by state-of-the-art advancements in machine learning. These methods require a large quantity of labeled data, which is difficult to obtain and mostly costly ...
Mohamed-Ali Tnani +2 more
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Collaborative Feature Learning from Social Media
, 2015 Image feature representation plays an essential role in image recognition and related tasks. The current state-of-the-art feature learning paradigm is supervised learning from labeled data.
Fang, Chen +3 more
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Visual Causal Feature Learning [PDF]
, 2015 We provide a rigorous definition of the visual cause of a behavior that is broadly applicable to the visually driven behavior in humans, animals, neurons, robots and other perceiving systems. Our framework generalizes standard accounts of causal learning
Chalupka, Krzysztof +2 more
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Pooling-Invariant Image Feature Learning [PDF]
, 2013 Unsupervised dictionary learning has been a key component in state-of-the-art computer vision recognition architectures. While highly effective methods exist for patch-based dictionary learning, these methods may learn redundant features after the ...
Darrell, Trevor +2 more
core
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
, 2017 Learning sophisticated feature interactions behind user behaviors is critical in maximizing CTR for recommender systems. Despite great progress, existing methods seem to have a strong bias towards low- or high-order interactions, or require expertise ...
Guo, Huifeng +4 more
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Concept learning and feature interpretation [PDF]
Memory & Cognition, 2000 Models of categorization often assume that people classify new instances directly on the basis of the presented, observable features. Recent research, however, has suggested that the coherence of a category may depend in part on more abstract features that can link together observable features that might otherwise seem to have little similarity.
T L, Spalding, B H, Ross
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MHST: Multiscale Head Selection Transformer for Hyperspectral and LiDAR Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingThe joint use of hyperspectral image (HSI) and light detection and ranging (LiDAR) data has gained significant performance on land-cover classification. Although spatial–spectral feature learning methods based on convolutional neural networks and ...
Kang Ni +3 more
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Leveraging deep feature learning for handwriting biometric authentication [PDF]
International Journal of Research in Industrial EngineeringThe authentication of writers through handwritten text stands as a biometric technique with considerable practical importance in the field of document forensics and literary history.
Parvaneh Afzali +2 more
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