A computer-implemented system for processing real-time video using a discriminator network comprising a perception branch and an adversarial branch trained using a generator network, wherein the perception branch comprises a neural network trained to detect a feature-of-interest and a location associated with the detected feature-of-interest in an image frame, wherein the generator network comprises a neural network configured to generate artificial representations of the feature-of-interest, wherein the adversarial branch comprises a neural network that accepts representations as input and outputs indications of whether the input representation is artificial or true, the system comprising: an input port for directly receiving real-time video obtained from a medical image device; a first bus for transferring the directly received real-time video; at least one processor configured to receive the real-time video from the first bus, wherein the at least one processor is configured to implement the discriminator network, wherein the at least one processor is configured to perform object detection by applying the trained perception branch of the discriminator network on frames of the directly received real-time video, and overlay a border indicating a location of at least one detected object in the frames, wherein the overlaid border comprises a two-dimensional shape displayed around a region of the image including the at least one detected object, the overlaid border being displayed in a first pattern and/or color; a second bus for receiving the video with the overlaid border; an output port for outputting the video with the overlaid border from the second bus to an external display; and a third bus for directly transmitting the directly received real-time video to the output port upon receipt of an error signal from the at least one processor; and wherein the at least one processor is further configured to determine if the at least one detected object is a true positive or a false positive by applying the trained adversarial branch of the discriminator network, and modify the overlaid border to be displayed in a second pattern and/or color when the at least one detected object is a true positive and further modify the overlaid border to be displayed in a third pattern and/or color if the at least one detected object is a false positive. an input port for directly receiving real-time video obtained from a medical image device; a first bus for transferring the directly received real-time video; at least one processor configured to receive the real-time video from the first bus, wherein the at least one processor is configured to implement the discriminator network, wherein the at least one processor is configured to perform object detection by applying the trained perception branch of the discriminator network on frames of the directly received real-time video, and overlay a border indicating a location of at least one detected object in the frames, wherein the overlaid border comprises a two-dimensional shape displayed around a region of the image including the at least one detected object, the overlaid border being displayed in a first pattern and/or color; a second bus for receiving the video with the overlaid border; an output port for outputting the video with the overlaid border from the second bus to an external display; and a third bus for directly transmitting the directly received real-time video to the output port upon receipt of an error signal from the at least one processor; and wherein the at least one processor is further configured to determine if the at least one detected object is a true positive or a false positive by applying the trained adversarial branch of the discriminator network, and modify the overlaid border to be displayed in a second pattern and/or color when the at least one detected object is a true positive and further modify the overlaid border to be displayed in a third pattern and/or color if the at least one detected object is a false positive.