A large number of intelligent models for masked face recognition (MFR) has been recently
presented and applied in various fields, such as masked face tracking for people safety or …

Variations in the form of the human face, which plays a role in our individual identities and
societal interactions, have fascinated scientists and artists alike. Here, we review our current …

Deep learning has attracted wide attention recently because of its excellent feature
representation ability and end-to-end automatic learning method. Especially in clinical …

Background Recognizing learners' engagement during learning processes is important for
providing personalized pedagogical support and preventing dropouts. As learning …

Intracranial hemorrhage is a serious medical problem that requires rapid and often intensive
medical care. Identifying the location and type of any hemorrhage present is a critical step in …

Abstract The integration of Artificial Intelligence (AI) into dairy farm management through
biometric facial recognition of cows marks a significant milestone in livestock care. This …

Deep neural networks are sensitive to adversarial examples and would produce wrong
results with high confidence. However, most existing attack methods exhibit weak …

Because our civilization has relied on pesticides to fight weeds, insects, and diseases since
antiquity, the use of these chemicals has become natural and exclusive. Unfortunately, the …

Deep learning networks can be deceived by properly processing the noise into the image.
As a powerful method, feature space adversarial attack improves the transferability of …

Recently, face recognition became a key element in social cognition which is used in
various applications including human–robot interaction (HRI), pedestrian identification, and …