Science begins with observation. From the small discoveries to the bigger revelations, the rise of computer vision is helping the best minds to effectively observe, capture significant moments and generate meaning from valuable datasets.
We are only at the beginning of an AI-empowered journey in science, one full of possibilities. So, what is computer vision doing for the world so far? And how is it being used to accelerate discovery in life sciences?
A brief history of computer vision
To understand where we are going, we need to know where we have come from. Computer vision (CV) was first pioneered in the 1960s during a project at MIT. Larry Roberts is widely known to be the father of computer vision, following his work extracting 3D information from 2D images.
A few years later, Marvin Minksy experimented with this kind of intelligence to mimic the human brain. During the ‘90s, computer vision techniques were implemented for ATM machines to enhance surveillance, but it wasn’t until the late noughties that deep learning within computer vision was accelerated by none other than Google, of course.
How computer vision is already changing the world
On the surface, scrutinising a photograph might not seem particularly revolutionary, but for an increasing number of sectors, it is.
The neural networks that are weaved within computer vision mean that images are recognised, and the AI/deep learning component interprets meaning from its objects.
So, let’s look at how industries are using computer vision to add value and make meaning of their work, so far.
Manufacturing
Computer vision is being used in manufacturing processes to assist quality control. During inspection processes, this kind of artificial intelligence is being used to detect flaws and defects, alerting workers that the product is not up to standard.
The automotive industry has particularly benefitted from computer vision. Tesla, for example, has automated its product assembly line using computer vision to generate 3D modelling designs, identify product components, and maintain packaging standards.
Agriculture
There are multiple ways that computer vision is helping to empower the agricultural industry:
- Pest detection – Through camera-based crop monitoring systems, farmers can effectively identify, count and classify any tiny trespassers on their crops. This kind of pest management is cost-effective and reduces the need for harmful pesticide use.
- Yield monitoring – Being able to monitor the growth of your crops as a farmer is pretty important, not just for individual income, but it can ultimately help stave off bigger issues associated with poor crop yields. CV helps with crop yield estimation and allows for accurate and timely monitoring, the kind that humans are pretty lousy at… (it’s human nature, not error)
- Environmental monitoring – For livestock monitoring, soil health and composition, and farmland mapping, CV is an efficient way to monitor farmlands. Using technology also helps to overcome labour shortages and is a useful tool in the face of climate change.
- Phenotyping – This characterisation of crops is important for decision making in agriculture. Plant phenotyping through computer vision helps to gather information on the functioning of crops, what environments are best and insights into plant genetics. This, then, can also help with crop modelling.
Satellite imagery
Observing our world is one of the best ways we can navigate it. Real-time imaging is helping our civilisation to overcome some of its biggest obstacles. Computer vision in earth observation helps to monitor the effects of climate change, detect and mitigate catastrophes such as oil spills and wildfires, and support ESG reporting.
Computer vision provides overarching change intelligence, so, varying organisations who use it can better monitor progress and projects, and make decisions.
Computer vision in life sciences and healthcare
Life science is nothing if not intricate. Through the life sciences, we really begin to understand all the microscopic building blocks that make up our world.
AI-empowered computer vision enables these minute organisms to not only be accurately identified but monitored and analysed much more efficiently than can be achieved with the human eye alone.
Life sciences
Computer vision is helping scientists in revolutionary ways. For life sciences, this kind of machine learning is helping to capture cell segmentation, with microbiology research and embryo analysis, and offering high-detail proteomic tissue analysis – and we all love a bit of high-detail proteomic tissue analysis.
Pharmaceuticals
Computer vision has also supported many use cases in the pharmaceutical industry From quality control in pill manufacturing to predictive maintenance and monitoring, the pharmaceutical industry is seeing great benefits from Industry 4.0.
Healthcare
Computer vision is being used to diagnose liver, lung, bone and cardiovascular diseases, to guide surgeons during procedures to detect cancerous tumours, and to improve existing imaging methods – such as MRI and CT – and their analysis.
Phenomics
The living world is overwhelmingly complex. Life scientists can often be limited in their efforts, having to confine them to a set of observable traits in their study. However, phenomic datasets are “essential if we are to understand some of the most compelling but challenging questions in the study of ecology and evolution.” (Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology.)
Processing times and costs have hindered this field, and the manual collection of data is prone to error and difficult to reproduce. Computer vision is a promising tool that is helping to overcome these obstacles, collecting datasets on a vast scale.
We can understand that computer vision and Industry 4.0 are making great waves within life sciences and healthcare, but is it being utilised to its full potential?
Lumi is giving the lab what it’s missing
Lumi is the first of its kind, a lab eye able to capture everything that happens in your research and experimentation.
Connected to an integrated platform, Lumi digests your data and helps to transform it into something meaningful, offering insights for you and your colleagues.
Harnessing Industry 4.0, we are using computer vision in laboratory environments to make sure scientists can figure out what happened, as well as when, how and why it happened.
For lab science, the Lumi computer vision solution:
- Captures operational data
- Increases reproducibility
- Enhances quality control and auditing
- Gathers raw data and delivers value
- Supports automation
- Alleviates scientists of the mundane tasks – so they can focus on what matters
We can see that CV is being embraced by various industries, but often the humble lab is overlooked. Well, we’re bringing that techy goodness directly to lab scientists. We are using computer vision in the lab to solve a longstanding analytical bottleneck – accelerating scientific excellence.
Want to supercharge your scientists, using computer vision to make greater discoveries? Get in touch with us today to find out more or to book a demo.