Abstract: There is provided a method of training a machine learning model, comprising: extracting faces depicted in image(s), creating an age training dataset comprising records, each including a face and a ground truth label indicating whether the face is below a legal age, training an age component on the age training dataset for generating a first outcome indicative of a target face from the target streaming being below the legal age, creating a sexuality training dataset comprising records, each including image(s) and ground truth label indicative of sexuality depicted therein, training a sexuality component on the sexuality training dataset for generating a second outcome indicative of sexuality depicted in the target streaming, defining a combination component that receives an input of a combination of the first outcome and the second outcome, and generates a third outcome indicative of child sexual abusive materials (CSAM) depicted in the target streaming.

Abstract: There is provided a method of training a machine learning model, comprising: extracting faces depicted in videos, creating an age training dataset comprising records, each including a face and a ground truth label indicating whether the face is below a legal age, training an age component on the age training dataset for generating a first outcome indicative of a target face from the target video being below the legal age, creating a sexuality training dataset comprising records each including frame(s) and ground truth label indicative of sexuality depicted therein, training a sexuality component on the sexuality training dataset for generating a second outcome indicative of sexuality depicted in target frame(s) of the target video, defining a combination component that receives an input of a combination of the first outcome and the second outcome, and generates a third outcome indicative of child sexual abusive materials (CSAM) depicted in the target frame(s).

Abstract: There is provided a method of training a machine learning model, comprising: extracting faces from first images, creating an age training dataset comprising records each including a face and a ground truth label indicating whether the face is below a legal age, training an age component on the age training dataset for generating a first outcome indicative of a target face of the target image being below the legal age, creating a sexuality training dataset comprising second records each including a second image and ground truth label indicative of sexuality, training a sexuality component on the sexuality training dataset for generating a second outcome indicative of sexuality depicted in the target image, defining a combination component that receives an input of a combination of the first outcome and the second outcome, and generates a third outcome indicative of child sexual abusive materials (CSAM) depicted in the target image.