We are excited to present you our latest article on Computer Vision powered Spatial AI:
A case study on cutting faulty welding joints using artificial intelligence.
Artificial Intelligence is changing the way we do just about everything these days. From business, to health, to education and beyond. But it’s also becoming a powerful tool in the realm of scientific research, especially when it comes to physics, perhaps one of the most complex and abstract fields of advancing human knowledge.
What are Artificial Neural Networks (CNN)? Do they actually do something useful or are they just confusing? What is actual difference between Feed Forward and Recurrent Neural Networks (RNN)? How do they work? What are the differences between different types of layers? Let’s look at the types of layers, learning objectives, and results.
Artificial Intelligence is finding its way into different sectors of the economy. In this blog, we’ll talk about how AI can solve food processing issues and why it matters.
This case study examines the challenge of detecting retail inventory issues. The presentation covers the detection technology, a background on how it was used in an actual project, and a discussion of lessons learned.
Mood Board Search is a fun and easy way to train computers to recognize visual concepts. It’s a playful way to explore and analyze image collections using mood boards as your search query.
Labeling is important in the food and beverage industry because consumers aren’t going to buy a product if the label isn’t present and legible. Companies can lose money on a bad batch of labels and have no way of knowing what went wrong. At Visionify.ai, we helped our client solve this problem by using Labeling Dtechnology to detect if mislabeled bottles were produced. We took a process normally reserved for commercial printers, scaled it down, and created an economical solution for them.
Our customer was experiencing problems managing their warehouse inventory. They had already tried several solutions unsuccessfully before choosing our image recognition and machine-learning technology because it seemed to provide the most powerful and comprehensive solution.
Food contamination is one of the most significant issues of the modern world, with polluted water, degraded soil, and unsafe manufacturing practices being the biggest threats to food safety. While the world struggles to improve water and soil quality, food safety practices throughout the production and supply chain stages can significantly improve the quality of food safety.