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Domain generalization based on domain-specific adversarial learning
Deep learning models often suffer from degraded performance when the distributions of the training and testing data differ (i.e., domain shift)....
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Domain generalization for video anomaly detection considering diverse anomaly types
In intelligent video surveillance, anomaly detection is conducted to identify the occurrence of abnormal events by monitoring the video captured by...
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Humans display interindividual differences in the latent mechanisms underlying fear generalization behaviour
Human generalization research aims to understand the processes underlying the transfer of prior experiences to new contexts. Generalization research...
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Domain generalization by distribution estimation
Domain generalization generalizes a prediction model trained on multiple source domains to an unseen target domain. The source and target domains are...
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Generalization of procedural motor sequence learning after a single practice trial
When humans begin learning new motor skills, they typically display early rapid performance improvements. It is not well understood how knowledge...
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MixStyle Neural Networks for Domain Generalization and Adaptation
Neural networks do not generalize well to unseen data with domain shifts—a longstanding problem in machine learning and AI. To overcome the problem,...
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Regional Adversarial Training for Better Robust Generalization
Adversarial training (AT) has been demonstrated as one of the most promising defense methods against various adversarial attacks. To our knowledge,...
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Quality-Invariant Domain Generalization for Face Anti-Spoofing
Face Anti-Spoofing (FAS) plays a critical role in safeguarding face recognition systems, while previous FAS methods suffer from poor generalization...
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On generalization reducts in incomplete multi-scale decision tables
In reality, data is always arranged at multiple granularity levels. Multi-scale information tables were introduced from the viewpoint of granular...
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NP4G: Network Programming for Generalization
In recent years, the development of Artificial Intelligence systems using neural network has been remarkable. However, this method has low...
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Detecting facial manipulated images via one-class domain generalization
Nowadays, numerous synthesized images and videos generated by facial manipulated techniques have become an emerging problem, which promotes facial...
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Human-like systematic generalization through a meta-learning neural network
The power of human language and thought arises from systematic compositionality—the algebraic ability to understand and produce novel combinations...
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Stability and Generalization of Hypergraph Collaborative Networks
Graph neural networks have been shown to be very effective in utilizing pairwise relationships across samples. Recently, there have been several...
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A generalization of the classical Euler and Korteweg fluids
The aim of this short paper is threefold. First, we develop an implicit generalization of a constitutive relation introduced by Korteweg (1901) that...
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Bell’s Inequality, Its Physical Origins, and Generalization
AbstractA mathematical generalization is given of the famous Bell inequality, which arose in connection with the analysis of the classical...
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Optimizing latent graph representations of surgical scenes for unseen domain generalization
PurposeAdvances in deep learning have resulted in effective models for surgical video analysis; however, these models often fail to generalize across...
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Generalization of beneficial exposure effects to untreated stimuli from another fear category
Previous research has shown that fear associated with one stimulus often spreads to other stimuli with similar perceptual features as well as across...
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Efficient Attention for Domain Generalization
Deep neural networks suffer severe performance degradation when encountering domain shift. Previous methods mainly focus on feature manipulation in...
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Inter-feature Relationship Certifies Robust Generalization of Adversarial Training
Whilst adversarial training has been shown as a promising wisdom to promote model robustness in computer vision and machine learning, adversarially...
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CSDG-FAS: Closed-Space Domain Generalization for Face Anti-spoofing
Domain generalization based Face Anti-spoofing (FAS) aims to enhance its ability to work in unseen domains. Existing methods endeavor to extract a...
