The applications for computer vision are practically infinite, replicating any visual task—and with Chooch’s computer vision platform, it’s never been easier to deploy fast, highly accurate AI models for everything from defect detection to security to complex counting.
That’s why organizations of all sizes and industries are now applying computer vision to a wide range of tasks to improve efficiency and accuracy, boost their productivity, and cut costs.
Computer vision solutions from Chooch AI integrate training and deployment into a single AI platform, making it simpler than ever to get started.
Edge AI enables businesses to run AI models on a variety of embedded systems, creating a network of fast, lightweight, interconnected devices enhanced with computer vision capabilities.
To step back for a moment if necessary, computer vision is a subfield of artificial intelligence that seeks to give computers the ability to “understand” aspects of images and videos.
Below, we’ll discuss everything you need to know about computer vision—including how you can implement it for organization.
These days, nearly all computer vision models are built using a class of machine learning algorithms known as deep learning. The basic building block of deep learning is an artificial neuron, which is connected to other neurons in a system called an artificial neural network, a rough approximation of the human brain.
A single neural network may contain thousands, millions, or billions of neurons, which are organized into more complex layers or structures, depending on the network’s architecture. Each neuron receives signals from other neurons, performs a mathematical calculation on these inputs, and sends the result to other connected neurons. Neurons also have internal parameters known as “weights” that affect the strength of their output on the rest of the network.
Depending on the task, computer vision models are trained on large datasets of images and/or videos. For each input data point, the network produces a prediction as output, which is then compared against the ground-truth output. If the network’s prediction is incorrect, the weights of the neurons in the network are adjusted via a process known as backpropagation, making it more likely that the system will produce the correct answer next time.
Training computer vision models can be highly intensive in terms of both time and effort, since datasets for the task you want may not initially be available. For example, if you want to train an AI model to recognize human faces in an image, you’ll need a large dataset of images, each one annotated with the location of the face(s).
Chooch dramatically simplifies the AI model training process. From within the Chooch dashboard, you can easily annotate your images and videos with bounding boxes or polygons. Since having a large, diverse set of images is essential for peak performance, you can even use Chooch’s synthetic data and data augmentation features if you need to increase the size of your dataset
Once training is complete and the network has reached a satisfactory level of accuracy, the network’s architecture and weights are saved in a condensed format known as the “model.” You can then deploy this model in a production environment, e.g. in the cloud or on an edge device, and use it for real-world data.
With Chooch’s cutting-edge AI platform, it’s never been easier for anyone—regardless of technical skill or experience—to build and deploy powerful AI models. When you send an image or video to the Chooch API, the Chooch Smart Network selects the appropriate AI model and generates the relevant prediction.
You can train and deploy AI models on an extremely wide range of tasks, giving you a great deal of flexibility in how you use them. For example, consider a photo of an apple: you could train an AI model to distinguish apples from other fruits, to recognize the color of the apple (e.g. green), or even to determine the type of apple (e.g. Granny Smith).
The Chooch integrated, end-to-end AI platform generates highly accurate predictions in just a fraction of a second. Using imagery from cameras, drones, cell phones, medical imaging devices, and more, Chooch AI models can deliver results when and where you need them, whether on the edge or in the cloud.
Thanks to technological advances and new research in deep learning and neural networks, the field of computer vision has made great strides in both accuracy and speed, with state-of-the-art models that can equal or even exceed the performance of humans on many tasks.
According to forecasts by market intelligence firm Research & Markets, the global computer vision market is predicted to skyrocket from $16 billion in 2019 to $51 billion in 2026, with a breakneck annual growth rate of 26 percent.
Why is this? Because there’s real business value in AI and computer vision.
It’s no exaggeration to say that you can use computer vision for any kind of visual data—from still images to videos, from infrared to X-rays. You can train an AI model to recognize any kind of pattern or trait in this visual data—including objects, concepts, faces, actions, and more.
Need some ideas? The Chooch AI app (available for iPhone and Android) lets you demo some of our platform’s capabilities, all in the palm of your hand. The app can recognize over 200,000 classes of objects in still images and videos.
Whatever your field or industry, computer vision can help your organization thrive in a constantly evolving business landscape. Below, we’ll go over just three common use cases for computer vision: healthcare, workplace safety, and manufacturing.
The field of healthcare is using computer vision for a wide range of applications. Computer vision healthcare use cases include:
Workplace safety and security is another domain in which computer vision can be tremendously helpful and effective—and even save lives. Use cases for safety and security AI include:
Last but not least, computer vision for industrial and manufacturing AI is rapidly growing in popularity. The applications of computer vision in manufacturing include:
The field of computer vision spans many different subfields and tasks. Below is just a sampling of the most common types of computer vision:
We’ve barely scratched the surface of what’s possible with computer vision. Sectors such as media, geospatial, retail, and many more have all successfully implemented transformative computer vision solutions. No matter your company’s size and industry, computer vision can help you achieve greater efficiencies, cut costs, beat your competitors, and better serve your customers.
Are you looking to implement AI within your own organization? We’re here to assist with the next steps. Get in touch with Chooch’s team of AI experts for a chat about your business needs and objectives, or sign up today to create a free account on the Chooch platform.