The Power of Machine Learning
- Detect and count objects
- Identify anomalies
- Classify shapes and textures
- Find regions of interest in a
large image for closer review by expert
- Iteratively refine segmentation of an object
- Distinguish classes too complex for human experts
- Integrate other forms of data
Featured Remote Sensing Projects
Is Your Machine Learning Project Struggling to Create the Insights You Need?
Expectations Exceed Reality
The current hype in AI leads many projects to set an unreasonable target or unclear success criteria leading them to over promise and under deliver.
Machine learning appears accessible because of the availability of many open source toolkits. But once you get started, it can be difficult to decipher why a particular model isn’t working, leading to wasted time on unsuccessful approaches.
The challenge is that there is no one-size-fits-all solution. The best approach often takes a lot of experimentation, and the most efficient path is dependent on understanding your data.
Applications in remote sensing are often challenged by the lack of detailed annotations and images from multiple satellites. Accommodating all these complexities into a single solution requires advanced research techniques.
There should be an easier path to driving impact with machine learning.
Ensure the success of your project with a machine learning expert at your side.
Get the Most Out of Your Images
- Define clear goals and metrics of success
- Properly preprocess data for effective model training
- Iterate quickly to build momentum
- Get from a sufficient to an ideal solution to maximize impact
Ensure the Success of Your Project
Like you, I care about driving impact. I can help you navigate this confusing AI journey. With 15 years of machine learning experience, I’ve seen models that fail for a particular task and those that succeed. I have many tools in my toolbox and the research experience to create novel algorithms for unique situations.
My specialty is problems for which there is no existing packaged solution. I make use of today's most powerful machine learning tools - TensorFlow, Keras, PyTorch, sklearn, and others - to help you create a new solution based on images and any other available data.
I have designed algorithms to estimate greenhouse gas emissions from sources on Earth and find rocks and craters on Mars. Together, we can generate new insights from your project too.
Heather D. Couture
Consultant & Researcher
The Challenges of Real World Remote Sensing Data
The process for machine learning is empirical and iterative - hypothesize a model, test it, and improve it.
While many talented machine learning engineers can create and train a model, they may be inexperienced with the challenges posed by real world data. The complexities of multi-band images and noisy or missing labels are a whole different ball game than clean benchmark data sets.
Machine learning engineers may also lack the experience to identify unique aspects of data that, with a customized model, can improve predictions.
I have studied rocks and craters on Mars and greenhouse gas emissions on Earth. I have created new multi-band and multi-modal models to address novel challenges.
The same may be beneficial for your project, but you won’t know it without looking from the right perspective.
Is Deep Learning the Best Approach?
Deep learning is a game changer for many applications. The power of deep learning comes from its ability to find patterns in complex data - even patterns beyond the limits of human perception. It is a new way to gain insights from data. Similar to how we learn from experience, deep learning performs a task repeatedly, tweaking how it does it each time to improve the outcome.
But there are also many situations - like limited training data or interpretability requirements - in which more traditional machine learning might be best. I am well-versed in both methodologies and will help you strategize as your project, your data, and your goals evolve.