Adobe, Inc.

Ciena Corporation

Vikas Kumar

Nandan Jha

Sourabh Gupta

Ajay Bedi

Jean-Francois Vanreusel

Piyush Singh

Nishchey Arya

Srijan Sandilya

Rachit Gupta

Digital image ordering based on object position and aesthetics is leveraged in a digital medium environment. According to various implementations, an image analysis system is implemented to identify visual objects in digital images and determine aesthetics attributes of the digital images. The digital images can then be arranged in way that prioritizes digital images that include relevant visual objects and that exhibit optimum visual aesthetics.

Digital image ordering using object position and aesthetics

Dynamic thumbnails are described. Dynamic thumbnails provide a convenient and automated approach for providing thumbnails that are contextually relevant to a user. In at least some implementations, an input image is analyzed to generate tags describing objects or points of interest within the image, and to generate rectangles that describe the locations within the image that correspond to the generated tags. Various combinations of generated tags are analyzed to determine the smallest bounding rectangle that contains every rectangle associated with the tags in the respective combination, and a thumbnail is created. A user input is received and compared to the tags associated with the generated thumbnails, and a thumbnail that is most relevant to the user input is selected and output to the user.

Dynamic thumbnails

Sketch completion using machine learning in a digital medium environment is described. Initially, a user sketches a digital image, e.g., using a stylus in a digital sketch application. A model trained using machine learning is leveraged to identify and describe visual characteristics of the user sketch. The visual characteristics describing the user sketch are compared to clusters of data generated by the model and that describe visual characteristics of a set of digital sketch images. Based on the comparison, digital sketch images having visual characteristics similar to the user sketch are identified from similar clusters. The similar images are returned for presentation as selectable suggestions for sketch completion of the sketched object.

Sketch completion using machine learning

Technology related to improving synthesis of foreign regional nouns using personalized and culturally correct phonetic transcription is described. The technology includes systems and methods for generating personalized speech by receiving an input, the input including textual data, identifying a regional noun in the textual data, and determining a user accent classification based on a context of the input. The method may further include determining a personalized phonetic transcription of the regional noun corresponding to the user accent classification and using a phonetic inventory stored in a database and outputting the personalized phonetic transcription.

Method to synthesize personalized phonetic transcription

The present disclosure provides systems and methods for handling performance monitoring (PM) data in a database in a manner that supports different PM data sets from different network element (NE) device types in an integrated manner. The present invention defines a single database structure that can be utilized to store, handle, retrieve, etc. PM counters from multiple NEs including NEs of different types, e.g. SONET/SDH NE, DWDM NE, optical switch, Ethernet switch, etc. The single database enables an efficient mechanism to handle PM data in a uniform way across a network with different device types.

Growing community of inventors

New Delhi, India

Vikas Kumar