Abstract: An image recognizing apparatus includes a processor that controls first and second learning processes, the first learning process in second layers including holding, based on a large/small relation between neuron data size and parameter size of the second layer, in a memory area, an error gradient of parameters to be sent to the corresponding layer of the second layers; and the second learning process between first layers including holding, in a memory area of each first layers, an error gradient of parameters to be sent to the corresponding layer of the first layers, which is computed based on the error gradient or an error gradient of a previous layer of the first layers, based on a large/small relation between neuron data size and parameter size of the first layer.

Abstract: An information processing apparatus includes a memory and a processor coupled to the memory and configured to set a first memory region in the memory as a region to be used for input to a first intermediate layer of a layered neural network and for output from the first intermediate layer, set a second memory region in the memory as a buffer region for the first intermediate layer, execute a recognition process of storing, in the second memory region, characteristic data corresponding to a characteristic of an input neuron data item to the first intermediate layer, and execute a learning process of determining an error of the first intermediate layer using the characteristic data stored in the second memory region.

Abstract: An information processing device includes: a processor that executes a process, the process including: controlling a recognition process that performs, with respect to input neuron data, a hierarchical neural network operation including a weighting operation using a parameter and that holds the neuron data and the parameter of each layer of the neural network in each of memory areas; and performing, in a learning process of learning the parameter of each layer of the neural network from an error that is obtained from a recognition result, regarding the layer in which the neuron data and the parameter are held in the memory areas, control of calculating an error of the neuron data after calculating an error of the parameter.

Abstract: An image recognizing apparatus includes a processor that controls first and second learning processes, the first learning process in second layers including holding, based on a large/small relation between neuron data size and parameter size of the second layer, in a memory area, an error gradient of parameters to be sent to the corresponding layer of the second layers; and the second learning process between first layers including holding, in a memory area of each first layers, an error gradient of parameters to be sent to the corresponding layer of the first layers, which is computed based on the error gradient or an error gradient of a previous layer of the first layers, based on a large/small relation between neuron data size and parameter size of the first layer.