Building an Image-classification Library for Deep-learning Algorithms
The purpose of BILDA is to improve the detection rate of the detection algorithm we use.
Until now, the detection rate has been too low for it to be possible to use only analyzes from the algorithm.
This means that a third party must manually verify data that the algorithm cannot approve on its own.
By creating an application where other people can verify the data from the algorithm by simply swiping on images,
it is expected that the detection rate can be improved with up to 95% accuracy,
which will drastically reduce resources spent on manually verifying the data.
Financial Exposure Network Geometry
FENG use infrared drone data capture technology for solar panel inspections in combination with advanced feature detection and machine learning algorithms to identify defective solar cells and reduced performance.
Utilization of aerial robotics ensures swifter, safer, and more efficient and repetitive inspections for a fraction of the cost of traditional inspection methods. We then strategize using smart tools and global resources in order to understand the implications of every choice our clients can make.