Edge AI and the Internet of Things (IoT) are two cutting-edge technology trends that offer the potential to digitally transform your business:
Computer vision, and subfields of computer vision such as object detection and object recognition, can certainly be classified under machine learning, depending on how you build the computer vision model. IBM defines machine learning as“a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.”
Knowing how to assess the performance of a pattern recognition model is highly important for a wide variety of tasks in artificial intelligence, machine learning, and computer vision. Below, I’ll discuss some of the most widely used criteria for good pattern recognition systems.
This presentation by Michael Liou was part of the Open Systems Media AI Day, Deploying Vision Systems with AI Capabilities. Because of the proliferation of edge devices, computer vision is one of AI’s killer apps in the form of edge AI.
An application programming interface (API) is a set of functions and definitions that enables two different software applications or systems to communicate with each other. Without APIs, developers would need to write custom integrations and scripts in order for these systems to exchange information—a time-consuming and technically challenging process. Chooch’s computer vision API helps users get fast, highly accurate identifications of the objects and concepts in their visual content. Given an image or video, the Chooch computer vision API will return the requested output (e.g. the items or faces in an image), as well as the relevant pixel coordinates.
Early fire and smoke detection using AI for safety and security have massive benefits. The savings to life and property are much higher than the cost of deploying these models. Faster and more accurate AI-enabled fire detection can save lives and property which brings unparalleled value to Chooch AI customers and partners.
Görsel yapay zeka artık hayatımızda. Turkcell CEO’su Murat Erkan ve Chooch AI CEO’su Emrah Gültekin ile gerçekleşen sohbetin video kaydını izleyebilirsiniz. Hakan Erdemli (Chooch AI) moderatörlüğündeki bu söyleşide, yapay zeka ve bilgisayarlı görü ile elde edilecek hızlı ve anlık iş değerini keşfedin.
Chooch.ai, a company that tracks objects and actions using artificial intelligence, could pursue a public listing “soon” or in a few years, said Michael Liou, vice president of strategy and growth.
The potential applications of computer vision are nearly limitless: from counting the number of customers in a store to diagnosing complex medical issues. Practically any use case that involves visual data (i.e. images and videos) is suitable for computer vision, with state-of-the-art models often matching or exceeding human performance.
Railway operators must conduct routine inspections and maintenance of tracks, trains, and other equipment to ensure the safe operation of railways. Through these inspection and maintenance activities, railway operators prevent service interruptions and, most importantly, reduce the chances of catastrophic railway accidents by resolving some of the most common causes of accidents, such as train and equipment failures, track defects, and other issues.