Cortica Ltd.

Autobrains Technologies Ltd.

Eli Passov

Igal Raichelgauz

An integrated circuit with arrays of convolution units that include hardware convolution neural network units configured to perform efficient expansion process by parallelization. The integrated circuit includes multiple building blocks that include the arrays of convolution units, inputs, and outputs t.

Integrated circuit with hardward convolution neural network units for efficient expansion processes

An apparatus that may include a neural network processor, the neural network processor comprises multiple building blocks. Each of the at least some of the building blocks may include, may consist or may consist essentially of a channel split unit, a convolution unit, a concatenation unit, and a shuffle unit.

Convolutional neural network with building blocks

A method that may include training a student ODNN to mimic a teacher ODNN. The training may include calculating a teacher student detection loss that is based on a pre-bounding-box output of the teacher ODNN. The pre-bounding-box output of the teacher ODNN is a function of pre-bounding-box outputs of different ODNNs that belong to the teacher ODNN. The method may also include detecting one or more objects in an image, by feeding the image to the trained student ODNN; outputting by the trained student ODNN a student pre-bounding-box output; and calculating one or more bounding boxes based on the student pre-bounding-box output.

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Hod Hasharon, Israel

Eli Passov