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5134 results about "Network module" patented technology

A network module is a software module that implements a specific function in a network stack, such as a data link interface, a transport protocol, or a network application. A network module can be a provider module, a client module, or both, depending on where it is located in the network stack.

Modular Networked Light Bulb

Various methods of manufacturing a lighting apparatus and embodiments of a modular networked lighting apparatus are disclosed. One method defines a mechanical form factor with a minimum set of electrical connections for a networking module, builds a subassembly of the networked lighting apparatus, the subassembly comprising attachment points compatible with the mechanical form factor for the networking module and contacts for the minimum set of electrical connections for the networking module, installs a networking module into the subassembly of the networked lighting apparatus, the networking module compatible with a selected networking protocol for the networked lighting apparatus, completes the final assembly of the networked lighting module, and marks the networked lighting apparatus to indicate the selected networking protocol for the networked lighting apparatus. In some embodiments, the lighting apparatus may function without the networking module installed. One embodiment of the modular, networked light bulb has means for supporting and holding an electronics module conforming with a predetermined form factor in place, and means for allowing the electronics module to control at least a brightness level of the at least one LED. The modular networked light bulb may have a networked controller conforming with the predetermined form factor used as the electronics module. The networked controller is able to connect to a network and may be positioned and held by the means for supporting and holding an electronics module.
Owner:SIGNIFY HLDG BV

Character recognition system and method based on combination of neural network and attention mechanism

The invention claims to protect a character recognition system and method based on the combination of a neural network and an attention mechanism, the system comprising: a convolution neural network feature extraction module, which is used for spatial feature of character image; The spatial features extracted by the convolution neural network are input to the bi-directional long-short memory network module, and the bi-directional long-short memory network can extract the sequence features of characters. The extracted feature vectors are semantically encoded, and then the attention weights of feature vectors are assigned through the attention mechanism, so that the attention is focused on the feature vectors with higher weights. In the decoding part of the model, the features extracted fromattention and the prediction information of the previous time are used as the inputs of the nested long-short memory network. The purpose of using the long-short memory network is to keep the temporal characteristics of the eigenvectors and make the attention points of the model constantly change with time. In the decoding part, the features extracted from attention and the prediction informationof the previous time are used as the inputs of the nested long-short memory network. The invention can more accurately detect the text area in the natural scene, and has good detection effect on thesmall target text and the text with small tilt angle.
Owner:CHONGQING UNIV OF POSTS & TELECOMM

Neural network system and method for controlling information output based on user feedback

A system and method for controlling information output based on user feedback about the information is provided that comprises a plurality of information sources providing information. The information sources may be electronic mail providers, chat participants, or page links. At least one neural network module selects one or more of a plurality of objects to receive information from the plurality of information sources based at least in part on a plurality of inputs and a plurality of weight values during that epoch. At least one server, associated with the neural network module, provides one or more of the objects to a plurality of recipients. The objects may comprise electronic mail messages, chat participants viewers, or slots within a link directory page. The recipients provide feedback about the information during an epoch. At the conclusion of an epoch, the neural network takes all of the feedback that has been provided from the recipients and generates a rating value for each of the plurality of objects. Based on the rating value and the selections made, the neural network redetermines the weight values within the network. The neural network then selects the objects to receive information during a subsequent epoch using the redetermined weight values and the inputs for that subsequent epoch.
Owner:HYPER SEARCH LLC
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