In Oil and gas, an industry characterized by intricate and hazardous operations, the battle against safety risks is ongoing and formidable. Fires, exposure to toxic gasses, malfunctioning equipment, and various environmental perils are ever-present threats endangering personnel and the natural world. These industries operate under severe conditions, necessitating adherence to stringent safety regulations and adopting … Read more
In today’s rapidly evolving industrial landscape, the need for advanced safety protocols is paramount. As the complexities of safety regulations continue to increase, the need for smart, automated solutions is becoming critically important. Talking about creating safer work environments, one key component that helps minimize exposure to workplace hazards and injuries is Personal Protective Equipment … Read more
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.
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.
Product labels create a product’s first impression. This is where consumers determine the look, feel, and taste of a product. Food and beverage labels usually contain origin, date and expiry, amount or volume, and class. To leverage product-specific data to improve supply chain management and prevent food fraud at points of sale, these labels must be recognized automatically.