Amazon Technologies, Inc.

Emc IP Holding Company LLC

Santosh Kumar Sahu

Ria Chakraborty

Vinod Durairaj

Sathish Kumar Ponnusamy

Madhur Popli

Rishi Kishore Verma

Pranesh Bhimarao Kaveri

C Manian Gandhi

Chaitra C N

Rachit Lamba

Suren Kumar J

Rohit Kamal Saxena

Techniques are generally described for machine learning exampled-based annotation of image data. In some examples, a first machine learning model may receive a query image comprising a first depiction of an object-of-interest. In some examples, the first machine learning model may receive a target image representing a scene in which a second depiction of the object-of-interest is visually represented. In various examples, the first machine learning model may generate annotated output image data that identifies a location of the second depiction of the object-of-interest within the target image. In some examples, an object detection model may be trained based at least in part on the annotated output image data.

Example-based image annotation

Devices and techniques are generally described for content classification. In some examples, first item data representing a first item may be received. The first item data may include a plurality of prediction scores output by a machine learning model. Each prediction score of the plurality of prediction scores may be associated with a respective label of a plurality of labels. In some examples, a set of one or more labels among the plurality of labels may be predicted. The set of labels may be predicted as being applicable to the first item for classification of the first item. A determination may be made that the set of one or more labels represents a complete set of labels applicable to the first item. In some examples, the first item may be classified based on the set of one or more labels.

Enabling automatic classification for multi-label classification problems with label completion guarantees

A method and system for intelligent power distribution management. Specifically, the disclosed method and system propose allocating (and deallocating) reserve or supplemental electrical power to host devices dynamically based on intelligent analyses of host device telemetry including, but not limited to, workload criticality, workload computing resource utilization, hardware configuration metadata, various operational parameters describing host device state, and measurements (as well as other information) pertinent to electrical power usage.

Method and system for intelligent power distribution management

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Bengaluru, India

Santosh Kumar Sahu