1. A computer-implemented method, comprising: obtaining image data that includes representations of text; determining a plurality of regions of interest, a first set of the plurality of regions of interest including the representations of text and a second set of the plurality of regions of interest including potential representations of text; using a first trained neural network to identify the first set of the plurality of regions of interest; using a second trained neural network to update a position of each region of the first set of the plurality of regions of interest to include respective text representations within a predetermined deviation; using a third trained neural network on the first set of the plurality of regions of interest to recognize words associated with respective regions based at least in part on the respective text representations; receiving a selection of one of a recognized word from the list of recognized words; causing a query to be executed against a data source, the query including the recognized word; receiving, in response to the query, result information for a set of items, the set of items determined by comparing the word to a library of words, each word in the library of words associated with at least one item; and generating a list of recognized words.
1. A computer-implemented method, comprising: obtaining image data that includes representations of text; determining a plurality of regions of interest, a first set of the plurality of regions of interest including the representations of text and a second set of the plurality of regions of interest including potential representations of text; using a first trained neural network to identify the first set of the plurality of regions of interest; using a second trained neural network to update a position of each region of the first set of the plurality of regions of interest to include respective text representations within a predetermined deviation; using a third trained neural network on the first set of the plurality of regions of interest to recognize words associated with respective regions based at least in part on the respective text representations; receiving a selection of one of a recognized word from the list of recognized words; causing a query to be executed against a data source, the query including the recognized word; receiving, in response to the query, result information for a set of items, the set of items determined by comparing the word to a library of words, each word in the library of words associated with at least one item; and generating a list of recognized words. 8. The computer-implemented method of claim 1 , wherein the image data is analyzed using a region proposal component operable to determine the plurality of regions of interest, a region filtering component operable to determine a subset of the plurality of regions of interest, a region refining component operable to refine position coordinates associated with each of the subset of the plurality of regions of interest, a text recognizer component operable to recognize words in the subset of the plurality of regions of interest, and a post-processing component operable to suppress overlapping regions of interest to determine a final set of regions of interest.