Abstract: An apparatus and a method for performing azimuth angle estimation are realized in which an object region or only an object region of a specific type is used as an azimuth angle estimation target region. There are provided: an azimuth angle estimation region selection unit configured to be inputted with a speed-range map indicating a distance and a relative speed of an object having reflected a radar wave, and select an azimuth angle estimation target region from the inputted speed-range map; and an azimuth angle estimation unit configured to execute azimuth angle estimation for only a selected region. The azimuth angle estimation region selection unit detects, from the speed-range map, a cluster that is an aggregate of bright spots and satisfies a predetermined condition, and selects the detected cluster as the azimuth angle estimation target region.

Abstract: The present technology relates to an information processing method, a program, and an information processing apparatus capable of analyzing a learning situation of a model using a neural network. In step S1, feature data that numerically represents a feature of a feature map generated from input data in a model using a neural network is generated. In step S2, analysis data based on the feature data of a plurality of the feature maps is generated. The present technology can be applied to, for example, a system that recognizes a vehicle in front of a vehicle.

Abstract: A binarized neural network circuit includes: an input part configured to allow input of input values (binary) and weights; an XNOR gate circuit configured to receive the input values and the weights and take XNOR logic; a multibit bias input part configured to allow input of a multibit bias; a sum circuit part configured to sum each of XNOR logical values and the multibit bias; and an activation circuit part configured to output only a sign bit of a multibit signal generated by using the sum.