Litcius/Paper detail

ReViT: Enhancing vision transformers feature diversity with attention residual connections

Anxhelo Diko, Danilo Avola, Marco Cascio, Luigi Cinque

2024Pattern Recognition38 citationsDOI

Topics & Concepts

ResidualComputer scienceFeature (linguistics)Artificial intelligenceComputer visionTransformerPattern recognition (psychology)EngineeringAlgorithmElectrical engineeringLinguisticsVoltagePhilosophyAdvanced Neural Network ApplicationsCurrency Recognition and DetectionVisual Attention and Saliency Detection
ReViT: Enhancing vision transformers feature diversity with attention residual connections | Litcius