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Preserving fairness generalization in deepfake detection
Although effective deepfake detection models have been developed in recent years recent
studies have revealed that these models can result in unfair performance disparities among …
studies have revealed that these models can result in unfair performance disparities among …
Improving fairness in deepfake detection
Despite the development of effective deepfake detectors in recent years, recent studies have
demonstrated that biases in the data used to train these detectors can lead to disparities in …
demonstrated that biases in the data used to train these detectors can lead to disparities in …
Eyes tell all: Irregular pupil shapes reveal gan-generated faces
Generative adversarial network (GAN) generated high-realistic human faces are visually
challenging to discern from real ones. They have been used as profile images for fake social …
challenging to discern from real ones. They have been used as profile images for fake social …
Learning a deep dual-level network for robust DeepFake detection
Face manipulation techniques, especially DeepFake techniques, are causing severe social
concerns and security problems. When faced with skewed data distributions such as those …
concerns and security problems. When faced with skewed data distributions such as those …
Robust attentive deep neural network for detecting gan-generated faces
Generative Adversarial Network (GAN) based techniques can generate and synthesize
realistic faces that cause profound social concerns and security problems. Existing methods …
realistic faces that cause profound social concerns and security problems. Existing methods …
Rank-based decomposable losses in machine learning: A survey
Recent works have revealed an essential paradigm in designing loss functions that
differentiate individual losses versus aggregate losses. The individual loss measures the …
differentiate individual losses versus aggregate losses. The individual loss measures the …
Tkml-ap: Adversarial attacks to top-k multi-label learning
Top-k multi-label learning, which returns the top-k predicted labels from an input, has many
practical applications such as image annotation, document analysis, and web search …
practical applications such as image annotation, document analysis, and web search …
Robust light-weight facial affective behavior recognition with clip
Human affective behavior analysis aims to delve into human expressions and behaviors to
deepen our understanding of human emotions. Basic expression categories (EXPR) and …
deepen our understanding of human emotions. Basic expression categories (EXPR) and …
Robust covid-19 detection in ct images with clip
In the realm of medical imaging, particularly for COVID-19 detection, deep learning models
face substantial challenges such as the necessity for extensive computational resources, the …
face substantial challenges such as the necessity for extensive computational resources, the …
UU-Mamba: uncertainty-aware u-mamba for cardiac image segmentation
Biomedical image segmentation is critical for accurate identification and analysis of
anatomical structures in medical imaging, particularly in cardiac MRI. Manual segmentation …
anatomical structures in medical imaging, particularly in cardiac MRI. Manual segmentation …