SYSTEM AND METHOD FOR DETECTING ABNORMALITY IDENTIFIERS BASED ON SIGNATURES GENERATED FOR MULTIMEDIA CONTENT ELEMENTS
A method for detecting abnormality identifiers based on multimedia content element signatures. The method includes causing generation of at least one signature for at least one input multimedia content element, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata representing the concept; comparing the generated at least one signature to a plurality of signatures of a plurality of reference multimedia content elements to determine at least one matching reference multimedia content element; and detecting, based on the comparison, at least one abnormality identifier for the at least one input multimedia content element.
1 . A method for detecting abnormality identifiers based on multimedia content element signatures, comprising:
causing generation of at least one signature for at least one input multimedia content element, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata representing the concept;
comparing the generated at least one signature to a plurality of signatures of a plurality of reference multimedia content elements to determine at least one matching reference multimedia content element; and
detecting, based on the comparison, at least one abnormality identifier for the at least one input multimedia content element.
2 . The method of claim 1 , wherein the signatures of each matching reference multimedia content element match the at least one signature generated for the at least one input multimedia content element above a predetermined threshold.
3 . The method of claim 1 , wherein detecting the at least one abnormality identifier further comprises:
sending, to a deep content classification system, at least one of: the at least one input multimedia content element, and the at least one signature generated for the at least one input multimedia content element;
receiving, from the deep concept classification system, at least one concept matching the at least one input multimedia content element; and
creating at least one abnormality identifier for the input multimedia content element, wherein each created abnormality identifier includes at least a portion of the metadata representing the matching at least one concept.
4 . The method of claim 1 , wherein each reference multimedia content element is associated with at least one predetermined abnormality identifier, wherein the detected at least one abnormality identifier includes the at least one predetermined abnormality identifier of each matching reference multimedia content element.
5 . The method of claim 1 , wherein the at least one reference multimedia content element includes at least one normal reference multimedia content element featuring at least one baseline identifier, wherein each abnormality identifier is detected with respect to a difference between one of the at least one baseline identifier and the at least one input multimedia content element.
6 . The method of claim 1 , further comprising:
searching, using the detected at least one abnormality identifier, for at least one potential disease.
7 . The method of claim 6 , wherein the at least one potential disease includes a plurality of potential diseases, further comprising:
sending, to a user device, a list of the plurality of potential diseases, wherein the list is organized based on at least one of: a degree of commonness of each potential disease, and a degree of matching between corresponding portions of each input multimedia content element and each reference multimedia content element.
8 . The method of claim 1 , wherein each input multimedia content element is at least one of: an image, graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, images of signals, and a portion thereof.
9 . The method of claim 1 , wherein each signature is generated by a signature generator system, wherein the signature generator system includes a plurality of at least partially statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core.
10 . A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process, the process comprising:
causing generation of at least one signature for at least one input multimedia content element, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata representing the concept;
comparing the generated at least one signature to a plurality of signatures of a plurality of reference multimedia content elements to determine at least one matching reference multimedia content element; and
detecting, based on the comparison, at least one abnormality identifier for the at least one input multimedia content element.
11 . A system for detecting abnormality identifiers based on multimedia content element signatures, comprising:
a processing circuitry; and
a memory connected to the processing circuitry, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
cause generation of at least one signature for at least one input multimedia content element, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata representing the concept;
compare the generated at least one signature to a plurality of signatures of a plurality of reference multimedia content elements to determine at least one matching reference multimedia content element; and
detect, based on the comparison, at least one abnormality identifier for the at least one input multimedia content element.
12 . The system of claim 11 , wherein the signatures of each matching reference multimedia content element match the at least one signature generated for the at least one input multimedia content element above a predetermined threshold.
13 . The system of claim 11 , wherein the system is further configured to:
send, to a deep content classification system, at least one of: the at least one input multimedia content element, and the at least one signature generated for the at least one input multimedia content element;
receive, from the deep concept classification system, at least one concept matching the at least one input multimedia content element; and
create at least one abnormality identifier for the input multimedia content element, wherein each created abnormality identifier includes at least a portion of the metadata representing the matching at least one concept.
14 . The system of claim 11 , wherein each reference multimedia content element is associated with at least one predetermined abnormality identifier, wherein the detected at least one abnormality identifier includes the at least one predetermined abnormality identifier of each matching reference multimedia content element.
15 . The system of claim 11 , wherein the at least one reference multimedia content element includes at least one normal reference multimedia content element featuring at least one baseline identifier, wherein each abnormality identifier is detected with respect to a difference between one of the at least one baseline identifier and the at least one input multimedia content element.
16 . The system of claim 11 , wherein the system is further configured to:
search, using the detected at least one abnormality identifier, for at least one potential disease.
17 . The system of claim 16 , wherein the at least one potential disease includes a plurality of potential diseases, wherein the system is further configured to:
send, to a user device, a list of the plurality of potential diseases, wherein the list is organized based on at least one of: a degree of commonness of each potential disease, and a degree of matching between corresponding portions of each input multimedia content element and each reference multimedia content element.
18 . The system of claim 11 , wherein each input multimedia content element is at least one of: an image, graphics, a video stream, a video clip, an audio stream, an audio clip, a video frame, a photograph, images of signals, and a portion thereof.
19 . The system of claim 11 , wherein each signature is generated by a signature generator system, wherein the signature generator system includes a plurality of at least partially statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core.
20 . The system of claim 11 , further comprising:
a signature generator system, wherein each signature is generated by the signature generator system, wherein the signature generator system includes a plurality of at least partially statistically independent computational cores, wherein the properties of each core are set independently of the properties of each other core.