Mosaic Data Science is building easily deployed custom AI applications powered by deep learning to automate tasks that normally require human vision.
Computer Vision | AI within reach
Computer vision is a field of artificial intelligence that trains a computer to extract the kind of information from images that would normally require human vision.
The goal of these deep learning models is not only to see, but also process and provide useful results based on the observation.
Machines can accurately classify and summarize images, identify objects, find similar images, and more. With the right application, they can react to what they see and automate a traditionally time-consuming process.
Mosaic will fit a solution to you & your business processes, not the other way around.
We build custom deep learning models to track any asset class in real-time.
Mosaic’s computer vision solutions can help you automate human vision tasks.
Businesses are adopting machine vision, yet many experience challenges
According to the leading market research firm Statista – the computer vision market is expected to grow to $30B in annual revenue by 2025.
Based on the latest media hype, you might think a business can just point convolutional neural networks at a problem, and presto, they have machines classifying images. In reality, properly designing and deploying a functional computer vision system involves complex steps that require significant expertise to carry out successfully.
It is very challenging for a single piece of software to solve multiple use cases. Each organization’s data is quite different. A Fast R-CNN might fit a set of data inputs for one use case, while a SSD is better at identifying a different set of images. If you are going for competitive advantage, why not build something powerful & unique to your business?
Without understanding the mechanics behind these models, you run the risk of not understanding the outputs, not being able to tune the model or not being able to translate analytics to business terms. You’ll spend a lot of time and money on a failed project if you don’t rely on the experts.
Many companies have failed to properly use computer vision because they lack the required experience. Experts with significant computer vision experience can help you create models that are adaptive and customizable, with understandable outputs and analytics that translate to business value.
Mosaic has helped several customers put machine vision to work for them.
Transportation firms utilize these computer vision algorithms to facilitate real-time routing, biomarker analysis and drone integration.
Energy companies need to conduct inspections on their physical infrastructure, computer vision more accurately predicts degradation & alerts maintenance.
Manufacturers can train deep learning models to identify defects in their manufacturing processes, boosting throughput efficiency.
Computer vision excels at identifying unique people using facial recognition. Low hanging fruit include the use cases around security, loyalty and segmentation.
Computer Vision can significantly improve the customer experience when navigating an eCommerce website. Improving filters provides a more seamless experience for users and boosts SEO rankings.
By training AI to accurately identify related images, these models can save researchers valuable time by quickly clustering similar images.
Mosaic can build you a powerful, custom computer vision solution. Our data scientists are experts at the deep learning development needed to train these machines. Our data engineers can help gather and organize your data. Our software engineers can integrate your computer vision models with products and deploy them in a scalable infrastructure.
Buying an out of the box solution might sound nice, but tuning deep learning takes substantial customization from an experienced data scientist. If a company promises you an out of the box solution to classify images, they do not understand the complexity of computer vision or artificial intelligence and you run the risk of a black box that doesn’t work.
Mosaic works with our customers where they are. We frequently coach and mentor our customers even while solving critical business problems.
New to AI? Mosaic’s proof of concept engagements are incredibly effective.
Neural what? Our intro to computer vision blog provides a gentle introduction to this deep learning technique. Mosaic focuses on the explainability of AI & machine learning, we can unpack any black box.
Using a deep learning algorithm with poor performance? Mosaic specializes in explainable AI.
Are you experimenting with neural networks, but not sure how to tune them properly? In the white paper above, Mosaic explains rapid prototyping of a diverse set of deep learning algorithms to more accurately detect airport layouts.
How do we build data pipelines to support efficient automation and facilitate human acceptance?
Are you planning to deploy computer vision models but want to make sure you have the correct data architecture in place? Mosaic’s software engineers have been deploying algorithmic solutions since 2004. Our collaborative approach fits the AI around you, not the other way around.
Additional Computer Vision Resources
Computer vision sounds expensive. At Mosaic, we use existing infrastructure and leverage open source platforms to achieve significant cost savings. Mosaic is a proponent of custom software, believing this approach truly provides businesses with a unique competitive advantage. Effective computer vision and deep learning solutions must be customized to the specific customer domain and data. Off-the-shelf solutions simply can not provide the true benefits of computer vision.
Object detection in video has become a matter of routine, however, expanding these models to detect an object of your choosing requires many thousands, if not tens of thousands, of training examples. Few shot learners seek to make this process cheaper and easier by learning to detect new objects with only a small handful of examples (i.e. 1-30)
There are many companies offering services to annotate the data for you or offer paid tools that have extensive automation to speed up this process. Still, the focus here is on open-source tools available today. Each tool works well for each specific purpose. The key is not to know many tools but to know which tool will work best for your project and understand how to leverage it best.
Video demonstration of autonomous planning using speech recognition and ATC domain supervisory control of an unmanned aircraft in high fidelity simulation.
Mosaic provided an in-depth interview with one of our senior data scientists engineers who specializes in designing & deploying custom computer vision algorithms.
This paper presents a vision-based navigation solution for unmanned aircraft operations on airfield surfaces in GPS-denied environments. The solution combines measurements from a computer vision system and inertial sensors with an airport layout database to provide accurate real-time position determination on the airfield surface.
Computer Vision Fact Sheet
Mosaic compiled a sheet examining the rise of AI vision.
Computer Vision in 3 Steps
Finding an Image
Ingest images from various sources in real-time to be stored for analysis.
Data scientists train these deep learning models to identify thousands of labeled images. After training/validation automation can be easily deployed.
Understand the Outputs
After the artificial intelligence classifies the object, system provides outputs back to the user or another machine.