Intel Corporation

Omar Florez

Glen J Anderson

Rita H Wouhaybi

Giuseppe Beppe Raffa

Jonathan J Huang

David Israel Gonzalez Aguirre

Javier Felip Leon

Lama Nachman

Rahul C Shah

Saurav Sahay

Yen-kuang Chen

Julio Cesar Zamora Esquivel

Lenitra M Durham

Sangita R Sharma

Chieh-Yih Wan

Mahesh M Subedar

Rebecca Chierichetti

Douglas P Bogia

Junaith Ahemed Shahabdeen

Ashwini Asokan

Andrea E Johnson

Hong Lu

Freddie H Huang

Various systems and methods for implementing intelligent traffic management for vehicle platoons are described herein. A road controller system includes A road controller system comprising: a data store to store an active traffic policy; a processor subsystem to: determine a speed or platoon size of a vehicle platoon traveling on an area controlled by the road controller system; and determine a change to the speed or platoon size of the vehicle platoon, the change based on the active traffic policy; and a transceiver to transmit a control message to the vehicle platoon to implement the change to the speed or platoon size of the vehicle platoon.

Intelligent traffic management for vehicle platoons

A convolutional neural network for classifying time series data uses a dynamic context selection. In one example a method includes receiving a plurality of inputs of different sizes at a convolutional neural network, applying convolution and pooling to each of the inputs to provide a plurality of outputs of different sizes, changing the size of each of the outputs to a selected uniform size, reshaping each of the outputs to a vector, and fully connecting the vectors.

Dynamic context-selective convolutional neural network for time series data classification

In one example a management system for an autonomous vehicle, comprises a first image sensor to collect first image data in a first geographic region proximate the autonomous vehicle and a second image sensor to collect second image data in a second geographic region proximate the first geographic region and a controller communicatively coupled to the first image sensor and the second image sensor and comprising processing circuitry to collect the first image data from the first image sensor and second image data from the second image sensor, generate a first reliability index for the first image sensor and a second reliability index for the second image sensor, and determine a correlation between the first image data and the second image data. Other examples may be described.

Post-incident management for autonomous vehicles

Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.

Technologies for automated context-aware media curation

A mechanism is described for facilitating personal assistance for curation of multimedia and generation of stories at computing devices according to one embodiment. A method of embodiments, as described herein, includes receiving, by one or more capturing/sensing components at a computing device, one or more media items relating to an event, and capturing a theme from the one or more media items, where the theme is captured based on at least one of activities, textual content, and scenes associated with the event. The method may further include forming a plurality of story elements to generate a story relating to the event, where the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices.

Facilitating personal assistance for curation of multimedia and generation of stories at computing devices

Growing community of inventors

Sunnyvale, CA, United States of America

Omar Florez