Abstract: A method for searching an image database, comprising receiving an adulterated image of an object, the adulterated image including object annotations for visual reference, applying a first neural network to the adulterated image, correlating a result of the applying the first neural network with each image of a reference database of images, the result including an edited image of the object and each image of the reference database of images including a reference object, and selecting, as a matching image, at least one image of the reference database of images having correlation values above a threshold correlation value. The method may include applying a masking to the adulterated image. The masking may include performing, via a second neural network, object recognition on the adulterated image, applying, based on the object recognition, computer vision to detect callout features relative to bounding boxes, and generating a contour mask of the object.

Abstract: A method for searching an image database, comprising receiving an adulterated image of an object, the adulterated image including object annotations for visual reference, applying a first neural network to the adulterated image, correlating a result of the applying the first neural network with each image of a reference database of images, the result including an edited image of the object and each image of the reference database of images including a reference object, and selecting, as a matching image, at least one image of the reference database of images having correlation values above a threshold correlation value. The method may include applying a masking to the adulterated image. The masking may include performing, via a second neural network, object recognition on the adulterated image, applying, based on the object recognition, computer vision to detect callout features relative to bounding boxes, and generating a contour mask of the object.