I have the bit set of images(about 100 thousand) that are encoded (using a neural network) into a 512-bit vector. For example:
https://image1.png => [0,1,0,0,0, ... 1] // size = 512 bit
https://image2.png => [1,1,1,0,0, ... 0] // size = 512 bit
https://image3.png => [0,0,1,1,0, ... 1] // size = 512 bit
The task is to find very quickly from a set of similar images by the image (binary vector) sent by the user. I found a possible solution with Hamming distances, but I'm not sure about its speed with my set of images.
I would like to know if someone has encountered such a problem and knows what is better to use in this situation?