Job description
I am looking for a company that will undertake the implementation of two modules working in the same way in a mobile application using ML machine learning techniques.
1. We will create a test module using a dataset with 100 photos. This module can be supplemented with thousands of photos in the future. Using the camera from the phone, the application will recognize the object and return information from the NAME class of the object and its% representation of the probability of recognizing the object.
2. The second test module is to generate fourier transform photos based on the same 100 photos. The transform should be made from the smaller cutout area of the photo of the captured element. The functionality in the application should, after uploading the current photo, generate such an FFT transform of this area section and compare it with this dataset, returning the% probability representation.
These modules are tested and I take into account the fact that a larger number of photos will result in better recognition and percentage representation of the object. We can keep this small dataset on the desktop version of the system, but larger data should be uploaded to the server and used in the rest API mobile application.
Delivery time until 12/12/21
Learn more about the theme of photos and ovulation design on priv. I have sample photos for delivery.
