1. A method of facilitating logo recognition training of a neural network via an image training set generated based on one or more logos, the method being implemented by a computer system that comprises one or more processors executing computer program instructions that, when executed, perform the method, the method comprising: obtaining logo information associated with a rendering of a logo that is to be recognized via a neural network; generating images based on the logo information, each of the images comprising (i) content other than the logo and (ii) a given rendering of the logo integrated with the other content; processing, via the neural network, the images to generate predictions related to recognition of the logo for the images, the generated predictions comprising a predicted boundary structure indicating a predicted location of the logo in a first image of the images; causing, via a user interface, presentation of the predicted boundary structure on an area of the first image; obtaining a reference feedback set, the reference feedback set comprising reference indications related to recognition of the logo for the images, the reference indications comprising a reference indication corresponding to (i) a user-initiated movement of the predicted boundary structure to another area of the first image that is initiated via the user interface or (ii) a user-initiated resizing of the predicted boundary structure that is initiated via the user interface; and updating the neural network based the generated predictions and the reference feedback set such that the neural network is updated based on the predicted boundary structure and the reference indication corresponding to the user-initiated movement or resizing.
1. A method of facilitating logo recognition training of a neural network via an image training set generated based on one or more logos, the method being implemented by a computer system that comprises one or more processors executing computer program instructions that, when executed, perform the method, the method comprising: obtaining logo information associated with a rendering of a logo that is to be recognized via a neural network; generating images based on the logo information, each of the images comprising (i) content other than the logo and (ii) a given rendering of the logo integrated with the other content; processing, via the neural network, the images to generate predictions related to recognition of the logo for the images, the generated predictions comprising a predicted boundary structure indicating a predicted location of the logo in a first image of the images; causing, via a user interface, presentation of the predicted boundary structure on an area of the first image; obtaining a reference feedback set, the reference feedback set comprising reference indications related to recognition of the logo for the images, the reference indications comprising a reference indication corresponding to (i) a user-initiated movement of the predicted boundary structure to another area of the first image that is initiated via the user interface or (ii) a user-initiated resizing of the predicted boundary structure that is initiated via the user interface; and updating the neural network based the generated predictions and the reference feedback set such that the neural network is updated based on the predicted boundary structure and the reference indication corresponding to the user-initiated movement or resizing. 14. The method of claim 1 , further comprising: obtaining template images from a database, wherein generating the images comprises, for each template image of the template images, generating at least one of the images by integrating a given rendering of the logo with the template image.