Abstract: A computer-implemented method according to one embodiment includes performing object detection on a frame to identify a set of objects within the frame, and determining a location of each object of the set of objects within the frame. The method further includes constructing a code tree structure for the frame. The code tree structure defines the determined locations. A rule defining modifications to make to at least some of the objects is received and the code tree structure is crawled. The rule is applied to the objects during the crawling. The method further includes layering the modifications defined in the rule on the set of objects within the frame. A computer program product according to another embodiment includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Abstract: Numerous embodiments are disclosed for accessing redundant non-volatile memory cells in place of one or more rows or columns containing one or more faulty non-volatile memory cells during a program, erase, read, or neural read operation in an analog neural memory system used in a deep learning artificial neural network.

Abstract: Various examples of decoders and physical layout designs for non-volatile flash memory arrays in an analog neural system are disclosed. In one example, a system comprises a plurality of vector-by-matrix multiplication arrays in an analog neural memory system, each vector-by-matrix multiplication array comprising an array of non-volatile memory cells organized into rows and columns, wherein each memory cell comprises a word line terminal; a plurality of read row decoders, each read row decoder coupled to one of the plurality of vector-by-matrix multiplication arrays for applying a voltage to one or more selected rows during a read operation; and a shared program row decoder coupled to all of the plurality of vector-by-matrix multiplication arrays for applying a voltage to one or more selected rows in one or more of the vector-by-matrix multiplication arrays during a program operation.

Abstract: Various embodiments of word line decoders, control gate decoders, bit line decoders, low voltage row decoders, and high voltage row decoders and various types of physical layout designs for non-volatile flash memory arrays in an analog neural system are disclosed. Shared and segmented embodiments of high voltage row decoders are disclosed.

Abstract: Numerous embodiments for processing the current output of a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. The embodiments comprise a summer circuit and an activation function circuit. The summer circuit and/or the activation function circuit comprise circuit elements that can be adjusted in response to the total possible current received from the VMM to optimize power consumption.

Abstract: Numerous embodiments of analog neural memory arrays are disclosed. Certain embodiments contain improved mechanisms for pulling source lines down to ground expeditiously. This is useful, for example, to minimize the voltage drop for a read, program, or erase operation.

Abstract: Numerous embodiments of decoders for use with a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. The decoders include bit line decoders, word line decoders, control gate decoders, source line decoders, and erase gate decoders. In certain embodiments, a high voltage version and a low voltage version of a decoder is used.

Abstract: Numerous embodiments of decoders for use with a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. The decoders include bit line decoders, word line decoders, control gate decoders, source line decoders, and erase gate decoders. In certain embodiments, a high voltage version and a low voltage version of a decoder is used.

Abstract: Systems and methods of passing data via resource identifiers for resources are provided herein. A data processing system can receive a first request from a client device responsive to an interaction with a content item presented on a first resource. The content item can include a resource identifier referencing a second resource accessible via an application to be installed. The first request can include the resource identifier and a device identifier. The data processing system can receive a second request from the client device responsive to an execution of the installed application. The second request can include the device identifier and an application identifier. The data processing system can determine that the application is to receive the request identifier. The data processing system can provide the resource identifier to direct the application to access the second resource for presentation via the application.

Abstract: Systems and methods of passing data via resource identifiers for resources are provided herein. A data processing system can receive a first request from a client device responsive to an interaction with a content item presented on a first resource. The content item can include a resource identifier referencing a second resource accessible via an application to be installed. The first request can include the resource identifier and a device identifier. The data processing system can receive a second request from the client device responsive to an execution of the installed application. The second request can include the device identifier and an application identifier. The data processing system can determine that the application is to receive the request identifier. The data processing system can provide the resource identifier to direct the application to access the second resource for presentation via the application.

Abstract: Systems and methods of passing data via resource identifiers for resources are provided herein. A data processing system can receive a first request from a client device responsive to an interaction with a content item presented on a first resource. The content item can include a resource identifier referencing a second resource accessible via an application to be installed. The first request can include the resource identifier and a device identifier. The data processing system can receive a second request from the client device responsive to an execution of the installed application. The second request can include the device identifier and an application identifier. The data processing system can determine that the application is to receive the request identifier. The data processing system can provide the resource identifier to direct the application to access the second resource for presentation via the application.

Abstract: Various embodiments of word line decoders, control gate decoders, bit line decoders, low voltage row decoders, and high voltage row decoders and various types of physical layout designs for non-volatile flash memory arrays in an analog neural system are disclosed. Shared and segmented embodiments of high voltage row decoders are disclosed.

Abstract: Systems, methods, and apparatus for a graphical dining interface are disclosed. In one aspect, a device comprises a component image processor configured to generate a representation of at least one component of an item. The device further comprises an input device configured to receive an input from a user, where the input comprises a selection of a first component. The device further comprises an item image processor configured to generate a representation of the item, where the representation of the item comprises the representation of the first component.

Abstract: Numerous embodiments are disclosed for accessing redundant non-volatile memory cells in place of one or more rows or columns containing one or more faulty non-volatile memory cells during a program, erase, read, or neural read operation in an analog neural memory system used in a deep learning artificial neural network.

Abstract: Techniques for establishing a communication connection between a hub computing system and a back-end computing system; receiving, at the hub computing system and from an Open Data Protocol (OData) application that resides on a mobile communications device, a request for a landscape and statistics service providing information associated with the back-end computing system; registering, on the hub computing system, the landscape and statistics service as an OData service configured to be provided over an OData channel between the hub computing system and the mobile communications device; and providing, by the hub computing system, the landscape and statistics service to the OData application as the OData service over the OData channel.

Abstract: Numerous embodiments of decoders for use with a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. The decoders include bit line decoders, word line decoders, control gate decoders, source line decoders, and erase gate decoders. In certain embodiments, a high voltage version and a low voltage version of a decoder is used.

Abstract: Numerous embodiments for processing the current output of a vector-by-matrix multiplication (VMM) array in an artificial neural network are disclosed. The embodiments comprise a summer circuit and an activation function circuit. The summer circuit and/or the activation function circuit comprise circuit elements that can be adjusted in response to the total possible current received from the VMM to optimize power consumption.

Abstract: Systems, methods, and apparatus for a graphical dining interface are disclosed. In one aspect, a device comprises a component image processor configured to generate a representation of at least one component of an item. The device further comprises an input device configured to receive an input from a user, where the input comprises a selection of a first component. The device further comprises an item image processor configured to generate a representation of the item, where the representation of the item comprises the representation of the first component.

Abstract: Systems, methods, and apparatus for a graphical dining interface are disclosed. In one aspect, a device comprises a component image processor configured to generate a representation of at least one component of an item. The device further comprises an input device configured to receive an input from a user, where the input comprises a selection of a first component. The device further comprises an item image processor configured to generate a representation of the item, where the representation of the item comprises the representation of the first component.

Abstract: Techniques for establishing a communication connection between a hub computing system and a back-end computing system; receiving, at the hub computing system and from an Open Data Protocol (OData) application that resides on a mobile communications device, a request for a landscape and statistics service providing information associated with the back-end computing system; registering, on the hub computing system, the landscape and statistics service as an OData service configured to be provided over an OData channel between the hub computing system and the mobile communications device; and providing, by the hub computing system, the landscape and statistics service to the OData application as the OData service over the OData channel.