Abstract: System and method for reducing false negatives in object detection, including: extracting an object of interest from a respective image in a first set of training data that includes in distribution (ID) data. For each of the object of interest extracted from the respective image in the first set of training data: fusing the object of interest with an image from a second set of data that does not include any objects of interest to form a fused image; adding the fused image to the training data; and using the training data to train a detection model for object detection.

Abstract: System and method for reducing false negatives in object detection, including: extracting an object of interest from a respective image in a first set of training data that includes in distribution (ID) data. For each of the object of interest extracted from the respective image in the first set of training data: fusing the object of interest with an image from a second set of data that does not include any objects of interest to form a fused image; adding the fused image to the training data; and using the training data to train a detection model for object detection.

Abstract: A method and system of facilitating product research and development, comprising: obtaining respective product-related data from a plurality of data sources, including product-specific data for a plurality of products, and non-product-specific data including at least one of talent profile data and technology description data; performing topic extraction on the respective product-specific data and the non-product-specific data to obtain respective topics associated with the plurality of products and corresponding numerical statistics for the respective topics; performing sentiment analysis on the respective product-specific data for a plurality of products for the respective topics to obtain respective values of a measure of consumer sentiment corresponding to the respective topics for a respective product; and presenting an integrated sentiment review of a selected product based on the respective values of the measure of consumer sentiment corresponding to one or more of the respective topics for the selected