International Business Machines Corporation

Cognex Corporation

Matthew Leon Hill

John Richard Smith

Yuan-Chi Chang

Chung-Sheng Li

John Ronald Kender

Apostol Ivanov Natsev

Lexing Xie

Lawrence David Bergman

Vittorio R Castelli

William M Silver

Sanjay J Nichani

Adam Wagman

E John McGarry

Willard P Foster

Nigel John Foster

Bishwaranjan Bhattacharjee

Parijat Dube

Milind R Naphade

Michael Robert Glass

Patrick D Watson

Noel C Codella

Murray Scott Campbell

Jelena Tesic

Siyu Huo

Brian Michael Belgodere

Rong Yan

Charu Chandra Aggarwal

Kun-Lung Wu

Philip Shilung Yu

Sriram Kolinjivadi Padmanabhan

Min Wang

Shahram Ebadollahi

Quoc-Bao Nguyen

Brian Michael Landry

Whether to train a new neural network model can be determined based on similarity estimates between a sample data set and a plurality of source data sets associated with a plurality of prior-trained neural network models. A cluster among the plurality of prior-trained neural network models can be determined. A set of training data based on the cluster can be determined. The new neural network model can be trained based on the set of training data.

Training transfer-focused models for deep learning

A computer-implemented method for data labeling is provided. The computer-implemented method assigns pseudo-labels to unlabeled examples of data using a similarity metric on an embedding space to produce pseudo-labeled examples. A curriculum learning model is trained using the pseudo-labeled examples. The curriculum learning model trained with the pseudo-labeled examples is employed in in a fine-tuning task to enhance classification accuracy of the data.

Generating and augmenting transfer learning datasets with pseudo-labeled images

A system and method for analyzing visual memes includes identifying visual memes associated with at least one topic in a data source. The visual memes propagated over time are tracked to extract information associated with identified visual memes. The information associated with the visual memes is analyzed to determine at least one of generation, propagation, and use of the identified memes.

Visual meme tracking for social media analysis

A system and method for constructing a hierarchical multi-faceted classification structure includes organizing a plurality of visual categories into a multi-relational reference ontology that accounts for a plurality of different types of relationships. Media artifacts are categorized into the plurality of visual categories. The categories of artifacts are refined based on faceted ontology relationships or constraints from the multi-relational reference ontology. The multi-relational reference ontology and the one or more media artifacts with relationships are stored as the hierarchical multi-faceted classification structure in computer readable memory storage.

Multi-facet classification scheme for cataloging of information artifacts

Interoperability is enabled between participants in a network by determining values associated with a value metric defined for at least a portion of the network. Information flow is directed between two or more of the participants based at least in part on semantic models corresponding to the participants and on the values associated with the value metric. The semantic models may define interactions between the participants and define at least a portion of information produced or consumed by the participants. The determination of the values and the direction of the information flow may be performed multiple times in order to modify the one or more value metrics. The direction of information flow may allow participants to be deleted from the network, may allow participants to be added to the network, or may allow behavior of the participants to be modified.

Enabling interoperability between participants in a network

A system and method for analyzing video include segmenting video stored in computer readable storage media into keyframes. Near-duplicate keyframes are represented as a sequence of indices. The near-duplicate keyframes are rendered in a graphical representation to determine relationships between video content.

Using near-duplicate video frames to analyze, classify, track, and visualize evolution and fitness of videos

Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Method for fast, robust, multi-dimensional pattern recognition

Methods and apparatus are provided for rewriting queries during a database query processing operation to include auxiliary attributes not included in the original query, thus improving processing efficiency. For example, in one aspect of the invention, a technique for rewriting a query in a query processing operation includes the following steps. First, the query is processed in accordance with at least a portion of a data set, producing query results. Second, data attributes from the query results are analyzed. Finally, at least one new predicate from at least one auxiliary data attribute is appended on the query.

Method and apparatus for query rewrite with auxiliary attributes in query processing operations

A method and structure for storing information for one or more semantic objects derived from raw data. A semantic object extracted from the raw data and classified to comprise the semantic object is received, the received semantic object having one or more attributes. A summary of attributes of the semantic object by calculating one or more statistics of one or more of the one or more attributes of the received semantic object, a confidence level of the received semantic object that quantifies a degree of certainty that the received semantic object has been correctly classified and/or labeled; and a compact representation of raw data of the received semantic object are generated. Indexing information for one or more of the summary of attributes and the compact representation of the semantic object is generated. The semantic object, along with its associated summary of attributes, confidence level, compact representation, and indexing information, stored in a semantic object database associated with a database storing the raw data.

System and method for indexing, searching and retrieving semantic objects

A method and apparatus is disclosed that receives an input narrative in a particular media format, and produces therefrom a multimedia enriched version of the input narrative. In one embodiment, a method is provided for enriching an input narrative with multimedia content, wherein the method includes the step of selectively segmenting the input narrative to form queries pertaining to different portions or elements of the input narrative. The method further comprises retrieving multimedia artifacts from one or more multimedia repositories, wherein each retrieved multimedia artifact is associated with one of the queries, and selecting a subset of the retrieved multimedia artifacts, wherein the subset includes artifacts comprising different types of multimedia content. The input narrative is then combined with respective multimedia artifacts of the subset, in order to provide an enriched and enhanced narrative.

Method and apparatus for automatic multimedia narrative enrichment

A method and system for storing a semantic object includes summarizing the attributes of a semantic object, indexing the summary of attributes, and storing the summary of attributes and the index of the summary of attributes.

Systems and method for indexing, searching and retrieving semantic objects

Methods and apparatus for query rewrite with auxiliary attributes in query processing operations

Growing community of inventors

Yonkers, NY, United States of America

Matthew Leon Hill