Implementation of IBM Visual Recognition

IBM Visual Recognition services simply involved an automated neural network API which could recognize a compressed ZIP folder of negative and positive classifying images. More importantly, the Watson interface integrates a simplified model to further demonstrate the negative and positive classifier comparison. Following image collection of 60 broad negative and positive images (Amyloid/Tau positive-negative), the ZIP folders were processed into the beta Visual Recognition service. The following figure (1.3) reveals the process of negative and positive classification and user input in the API.