A method for performing a visual search based on a query image, the method comprising: applying a fractal transform to each image of a plurality of images in a dataset to generate a fractal map for each image; applying deep learning logic to the plurality of images to produce a feature set for each image of the plurality of images, wherein the feature set for each image of the plurality of images includes information associated with features of the image; storing information associated with the fractal transform and the feature set in association with a corresponding image, such that the fractal map of each image of the dataset is stored in association with the corresponding image and a feature set to produce a set of searchable images; receiving, by one or more processors, the query image; applying, by the one or more processors, the fractal transform to the query image to generate a fractal map of the query image; determining an immediate search space based on the fractal map of the query image, the immediate search space corresponding to a subset of the plurality of images, wherein the immediate search space is limited based on the fractal maps of the images in the dataset; applying, by the one or more processors, deep learning logic to the query image to produce a feature set for the query image, wherein the feature set includes information associated with features of the query image; and comparing the feature set for the query image to stored feature sets corresponding to images included in the immediate search space to identify a set of search results (504, 506, 508); wherein the set of search results (504, 506, 508) comprises one or more images having features similar to the query image; and outputting, by the one or more processors, the set of search results (504, 506, 508). applying a fractal transform to each image of a plurality of images in a dataset to generate a fractal map for each image; applying deep learning logic to the plurality of images to produce a feature set for each image of the plurality of images, wherein the feature set for each image of the plurality of images includes information associated with features of the image; storing information associated with the fractal transform and the feature set in association with a corresponding image, such that the fractal map of each image of the dataset is stored in association with the corresponding image and a feature set to produce a set of searchable images; receiving, by one or more processors, the query image; applying, by the one or more processors, the fractal transform to the query image to generate a fractal map of the query image; determining an immediate search space based on the fractal map of the query image, the immediate search space corresponding to a subset of the plurality of images, wherein the immediate search space is limited based on the fractal maps of the images in the dataset; applying, by the one or more processors, deep learning logic to the query image to produce a feature set for the query image, wherein the feature set includes information associated with features of the query image; and comparing the feature set for the query image to stored feature sets corresponding to images included in the immediate search space to identify a set of search results (504, 506, 508); wherein the set of search results (504, 506, 508) comprises one or more images having features similar to the query image; and outputting, by the one or more processors, the set of search results (504, 506, 508).