Intel Corporation

David Coates

Michael J Nolan

Keith A Ellis

Michael J McGrath

Giovani Estrada

Marcin Spoczynski

Niall Cahill

An apparatus is disclosed to compress packets, the apparatus comprising; a data analyzer to identify a new destination address and a protocol identifier of an input packet corresponding to a new destination node and a communication system between the new destination node and a source node; a compression engine to utilize a plurality of compression functions based on the new destination address and the protocol identifier and reduce a size of the input packet; a compression analyzer to identify a reduced packet and a compression function identifier corresponding to the reduced packet, the compression function identifier associated with one of the compression functions; and a source modifier to construct a packet to include the compression function identifier by modifying unregistered values of a protocol identifier by a difference associated with the compression function identifier, the packet to inform the new destination node of a compression function.

Methods and apparatus to compress packets in a computing environment

Methods, apparatus, systems and articles of manufacture to improve accuracy of a fog/edge-based classifier system are disclosed. An example apparatus includes a transducer to mounted on a tracked object, the transducer to generate data samples corresponding to the tracked object; a discriminator to: generate a first classification using a first model based on a first calculated feature of the first data samples from the transducer, the first model corresponding to calculated features determined from second data samples, the second data samples obtained prior to the first data samples; generate an offset based on a difference between a first model feature the first model and a second model feature of a second model, the second model being different than the first model; and adjust the first calculated feature using the offset to generate an adjusted feature; a pattern matching engine to generate a second classification using vectors corresponding to the second model based on the adjusted feature; and a counter to, when the first classification matches the second classification, increment a count.

Methods and apparatus to improve accuracy of edge and/or a fog-based classification

Methods, apparatus, systems, and articles of manufacture for conditional classifier chaining in a constrained machine learning environment are disclosed. An example apparatus includes a classification controller to select a first model to be utilized to classify a first feature identified from sensor data. A memory controller is to copy the first model to a memory. A machine learning processor is to apply the first model to the first feature to create a first classification output, the first classification output indicating an identified class. The classification controller is to, in response to a determination that the first classification output identifies a second model to be used for classification, instruct the memory controller to load the second model into the memory. The machine learning processor is to apply the second model to the second feature to create a second classification output.

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Leixlip, Ireland

David Coates