Vision Transformer (ViT)

What Is Vision Transformer (ViT)?

Vision Transformer (ViT) is an advanced neural network architecture that applies transformer models—originally developed for natural language processing—to visual data. Unlike traditional convolutional neural networks (CNNs), ViT divides images into patches and processes them as sequences, enabling the model to capture complex patterns and relationships across the entire image.

How Does Vision Transformer (ViT) Work?

1. Image Patch Embedding: The input image is split into fixed-size patches. Each patch is flattened and converted into a vector, similar to how words are embedded in language models.
2. Transformer Encoding: The patch embeddings are passed through multiple transformer layers. These layers use self-attention mechanisms to analyze relationships between patches, allowing the model to understand global context and subtle details within the image.
3. Classification and Output: The encoded information is aggregated and fed into a classification head, which predicts the image’s category or identifies objects. NYRIS uses ViT to process millions of images with high precision, even in challenging industrial environments.

Use Cases

• Manufacturing (Spare Parts Identification) Vision Transformer models enable instant recognition of spare parts from complex backgrounds, reducing machine downtime by up to 85%. NYRIS has deployed ViT-powered solutions for clients like DMG Mori and Trumpf.
• E-commerce (Visual Product Discovery) Shoppers can upload a photo to find visually similar products, improving conversion rates and customer satisfaction. NYRIS’s ViT-based search supports massive product catalogs, as seen with IKEA.
• Retail (Inventory Management \& Self-Checkout) Store associates and customers use mobile devices to scan products for real-time identification, streamlining inventory checks and checkout processes. NYRIS’s ViT technology enables sub-second recognition across 500 million items.

Benefits For Your Company

• Significant Reduction in Manual Processes Automate image-based identification, cutting manual effort by up to 85% and enabling staff to focus on higher-value tasks.
• Superior Accuracy Achieve recognition rates up to 99.7%, minimizing errors and ensuring reliable product or part identification.
• Scalable, Lightning-Fast Search Identify items within 0.5 seconds, even in databases with hundreds of millions of products—giving your business a competitive edge in speed and scalability.