Abstract

Systems and methods that yield highly-accurate classification of acoustic and other non-image events are disclosed, such as those involving pre-processing data from one or more transducers and/or generating a visual representation of the source as well as associated features and processing. In some implementations, such pre-processing may be utilized when 1) all impulsive acoustic events have many features in common due to their point source origin and/or impulsive nature, and/or 2) the error rates that are considered acceptable in general purpose image classification are much higher than the acceptable levels in automatic impulsive incident classification. Further, according to some aspects, data may be pre- processed in various ways, such as to remove extraneous or irrelevant details and/or perform any required rotation, alignment, scaling, etc. tasks, such that these tasks do not need to be otherwise "learned" via the neural network.

IPC Classes  ?

• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06T 11/60 - Editing figures and text; Combining figures or text