The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A ...

In the last decade, convolutional neural networks (CNNs) have been the go-to architecture in computer vision, owing to their powerful capability in learning representations from images/videos.

First, similar to how the Transformer works, the Vision Transformer is supervised, meaning the model is trained on a dataset of images and their corresponding labels. Convert the patch into a vector ...

Vision AI Has Moved Beyond CNNs—Now What? Convolutional Neural Networks (CNNs) have long dominated AI vision, powering applications from automotive ADAS to face recognition and surveillance. But the ...

Burlingame, CA – June 20, 2023 – Quadric® today announced that its Chimera TM general purpose neural processing unit (GPNPU) processor intellectual property (IP) supports vision transformer (ViT) ...

Vision transformers (ViTs) are powerful artificial intelligence (AI) technologies that can identify or categorize objects in images -- however, there are significant challenges related to both ...

At the Google Cloud Next conference, Google introduced a new computer vision platform, Vertex AI Vision, that simplifies the process of building analytics based on live camera streams and videos.