Create custom Deep Learning models to detect a variety of objects in images captured by drones with minimal data & limited knowledge of machine learning.
We have industry specific use cases and applications pre built to help you to get started quickly.
Monitor Diseases | Yield Protection | Water & Fertilizer distress
Solar panels | Wind turbines | Bridges | Oil refinery | Railways
Land surveying | Site management
Search & Rescue | Surveillance | Security
Shark detection | Wildlife conservation | Oil spill monitoring
Solar Plant Inspection
Nanonet's API allows for automated inspection of Solar Panels. We identify any defect in the panel reducing performance with severity, location and size. This can help companies easily maintain the performance of their solar panels.
16 JUNE 2018 | CONSTRUCTION
Fault Detection In Wind Turbines
Nanonet's can easily detect faults in Wind Turbines. Using our automated defect analysis, customers can cut down on cost of maintenance and inspection as well as greatly reducing turn around time.
16 JUNE 2018 | CONSTRUCTION
Below is an application demonstrating car detection in aerial images using NanoNets API.
Click one of the drone images in bottom to detect cars in them. Optionally upload your own aerial image with cars.
Automate and accurately detect faults or cracks on your machinery within your infrastructure - detect, classify and report.
Cover large areas in a quick turnaround time
Applications in :
Factories, Wind & Solar farms, Power infrastructure, Bridge, Tunnels, etc.
One of the primary problems in building Deep Learning models is not having enough labelled data to be able to train models. We reduce the data needed by 10x using Transfer Learning
We provide in-house annotators that have multiple years of experience working with aerial images. They will ensure that your images are labelled with high precision and consistency to better aid model training.
Re-training traditional pre-trained object detection models like Mobilenets and ResNets are not well suited for drone images. Our pre trained models have been trained using a large and diverse dataset of aerial images.
Every NanoNets model is made for just one company, YOU. We do not have anything that is built for a general use case. This enables us to build highly customized models.
By sharing our GPU costs across users we get much better utilization and hence our services are much cheaper then self hosting. Not to even compare to costs of humans performing these tasks.
Nanonets has a super easy to use API that integrates with whatever your backend and front end are written in. It usually takes a couple of lines of code to drop in. Even our self hosted solution works with a single line.
Step 1Upload Images
Nanonets allows users to train a model to detect custom objects specific to their need. 100 images minimum.
Step 2Create categories & Annotate
Add categories and annotate the objects to be detected on the images uploaded. 100 annotations per category minimum.
Step 3Train your model
Sit back & relax for a few minutes while we're training your model. We'll shoot an email to you as soon as it's ready.
Step 4Test & Integrate API
Query the cloud API to predict results on a test image. For more accuracy, add more data. Integrate into your product with a couple of lines of code.
Place upto a 1000 API Calls for 7 days. Pay as you go later.
We offer a fully managed solution that you can run either on your premises or on our premises.
Have one of our experts reach out to get a fully customized solution. Or schedule a demo.