Samsung Electronics Co., Ltd.

Won J Jeon

Simon J Gibbs

Pranav K Mistry

Bo Li

Abhijit Z Bendale

Lu Luo

Hyun Jae Kang

Jihee Kim

Anthony S Liot

Tasneem G Brutch

Zhihan Ying

Thomas Phan

Stanislaw Antol

A method includes retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof. At least one model is identified from multiple models based on the contextual information and at least one object recognized in an image based on at least one model. At least one icon is displayed at the device. The at least one icon being associated with at least one of an application, a service, or a combination thereof providing additional information.

System and method for contextual driven intelligence

One embodiment provides a method comprising classifying one or more objects present in an input comprising visual data by executing a first set of models associated with a domain on the input. Each model corresponds to an object category. Each model is trained to generate a visual classifier result relating to a corresponding object category in the input with an associated confidence value indicative of accuracy of the visual classifier result. The method further comprises aggregating a first set of visual classifier results based on confidence value associated with each visual classifier result of each model of the first set of models. At least one other model is selectable for execution on the input based on the aggregated first set of visual classifier results for additional classification of the objects. One or more visual classifier results are returned to an application running on an electronic device for display.

Vision intelligence management for electronic devices

In a first embodiment of the present invention, a method for enabling hardware acceleration of web applications is provided, comprising: parsing a web page using a scripting engine, wherein the web page necessitates running a web application; accessing one or more Application Program Interfaces (APIs) that provide parallelization, and distribute tasks of the web application among multiple cores of a multi-core central processing unit (CPU) or graphical processing unit (GPU), wherein the accessing uses a compute context class that, when instantiated, creates a compute context object that acts as a bridge between the scripting engine and the one or more APIs; and creating one or more kernels to operate on the multiple cores.

Hardware acceleration of web applications

A mobile handset device collects sensor data about the physiological state of the user of the handset. The mobile handset device receives multimedia content, which is consumed on the mobile handset. In a deployment phase, the sensor data is used to classify the user's emotional response to individual pieces of media content consumed on the mobile device. A classification model built in a training phase may be used to map sensor data to classification labels indicative of the user's emotional response to multimedia.

Using physical sensory input to determine human response to multimedia content displayed on a mobile device

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San Jose, CA, United States of America

Won J Jeon