Computer vision and artificial intelligence need a lot of data. The more volume and variety of data that you can show to your model during AI training, the more high-performance and robust the model will be when examining data in the real world that it hasn’t seen before. There’s just one issue: what if you only have a limited amount of data in the first place? That’s where data augmentation comes in.
Powered by artificial intelligence and machine learning, computer vision can help digitally transform your business. Today, sophisticated computer vision AI models can learn to recognize a wide variety of faces, objects, concepts, and actions, just as well as—if not even better than—humans can. But…
Imagine a manufacturing facility with a team of quality control inspectors that never get tired, never get distracted, and always perform their jobs with laser-point accuracy. Even better, these defect detection inspectors provide their services for a fraction of the usual cost.
The power of computer vision is poised to have a positive impact on the $3 trillion workers compensation space. AI models can help prevent 85% of injuries in the workplace – slip & fall, manual materials handling, tool accidents and struck-by’s. In this executive briefing, ADLINK, StrongArm Technologies and Chooch AI will discuss how the integration of their three technologies enables enterprises to detect the lack of safety gear and dangerous conditions and alert workers and management on a real time basis. Hear from leaders not only about the impact on costs and worker safety, but also the practical solution available now for the workplace.
This technology briefing covers the full lifecycle of dataset generation, AI model creation and deployment and inferencing on the edge. Emrah Gultekin, CEO of Chooch AI, presents case studies and a walkthrough of the AI platform.
Data collection is the first step in the process of generating a dataset for use in machine learning and computer vision training. Performing good data collection is essential to success: the quality of an AI model can only be as good as the quality of the dataset it’s trained on.
What is an AI model exactly, and how do you train AI models? Why are all AI models not created equally? Better training, using the right mix of algorithms and frameworks, and even setting the right business requirements, that’s how we achieve the highest performance when developing and deploying an AI model for computer vision.
In this 15 minute presentation, Emrah Gultekin, CEO of Chooch AI, presents how the Chooch AI platform ingests visual data, trains the AI, and exports AI models to the edge. This allows scalable inferencing on the edge on any number of devices from any number of cameras. A transcript of the presentation is provided below the video.
An AI (artificial intelligence) model is a program that has been trained on a set of data (called the training set) to recognize certain types of patterns. AI models use various types of algorithms to reason over and learn from this data, with the overarching goal of solving business problems. There are many different fields that use AI models with different levels of complexity and purposes, including computer vision, robotics, and natural language processing.