Recent years have seen a phenomenal rise in the performance and applications of
transformer neural networks. The family of transformer networks, including Bidirectional …

Over the past decade, the dominance of deep learning has prevailed across various
domains of artificial intelligence, including natural language processing, computer vision …

The continuously increasing number of traffic accidents necessitates addressing distracted
driving, which is responsible for numerous fatalities. Enhancing driver behavior recognition …

State-of-the-art deep learning models for computer vision tasks are based on the transformer
architecture and often deployed in real-time applications. In this scenario, the resources …

Many state-of-the-art deep learning models for computer vision tasks are based on the
transformer architecture. Such models can be computationally expensive and are typically …

With the great success of the Transformer model in Natural Language Processing (NLP),
Vision Transformer (ViT) was proposed achieving comparable performance to traditional …