Abstract: An information processing unit includes: an attention module having an attention layer and a computation section and that is for a neural network including plural levels of layer, the attention layer being configured to compute an output feature corresponding to an input feature from a predetermined layer and based on a parameter; the computation section that multiplies the input feature by the output feature, and outputs a computed result to a layer at a next level; the first learning unit connected to the neural network and that learns the parameter in a state in which learning has been suspended at least for the predetermined layer and the next level layer; and the channel selection section that selects as a redundant channel a channel satisfying a predetermined relationship between the output feature and a predetermined threshold value.

Abstract: There is provided a neural network reduction device including: an input section configured to acquire a first neural network including a plurality of processing layers that includes at least one convolutional layer; a generation section configured to generate a third neural network in which at least one second neural network is connected as an additional layer to a stage subsequent to the convolutional layer included in the first neural network; a learning section configured to train the third neural network; a correction section configured to select, as a redundant channel, a channel whose feature value calculated on a basis of a weight parameter of the second neural network establishes a predetermined relationship with a predetermined threshold, delete the redundant channel from the convolutional layer, and correct a weight parameter of the convolutional layer after deletion of the redundant channel on a basis of at least a portion of the weight parameter of the second neural network; a relearning section c

Abstract: It is possible to improve estimation accuracy with regard to data in which significance is attached to a relative phase. Provided is an information processing device including an estimation unit configured to estimate a status by using a neural network. The neural network includes a first complex-valued neural network to which complex data is input, a phase difference computation layer from which phase difference for each element between a plurality of sets with regard to the complex data is output, and a second complex-valued neural network from which complex data is output on the basis of the phase difference.

Abstract: There is provided a neural network reduction device including: an input section configured to acquire a first neural network including a plurality of processing layers that includes at least one convolutional layer; a generation section configured to generate a third neural network in which at least one second neural network is connected as an additional layer to a stage subsequent to the convolutional layer included in the first neural network; a learning section configured to train the third neural network; a correction section configured to select, as a redundant channel, a channel whose feature value calculated on a basis of a weight parameter of the second neural network establishes a predetermined relationship with a predetermined threshold, delete the redundant channel from the convolutional layer, and correct a weight parameter of the convolutional layer after deletion of the redundant channel on a basis of at least a portion of the weight parameter of the second neural network; a relearning section c

Abstract: An information processing unit includes: an attention module having an attention layer and a computation section and that is for a neural network including plural levels of layer, the attention layer being configured to compute an output feature corresponding to an input feature from a predetermined layer and based on a parameter; the computation section that multiplies the input feature by the output feature, and outputs a computed result to a layer at a next level; the first learning unit connected to the neural network and that learns the parameter in a state in which learning has been suspended at least for the predetermined layer and the next level layer; and the channel selection section that selects as a redundant channel a channel satisfying a predetermined relationship between the output feature and a predetermined threshold value.

Abstract: An estimation device includes a first converting unit configured to convert a beat signal to a one-dimensional first candidate signal on the basis of a two-dimensional distribution of the beat signal, a second converting unit configured to convert the beat signal to a one-dimensional second candidate signal on the basis of a two-dimensional position change of the beat signal, and a signal deciding unit configured to decide a one-dimensional signal on the basis of the first candidate signal and the second candidate signal.

Abstract: A tracking apparatus, including (1) a first target object tracking unit having a first processor, configured to correct a first information of at least one first candidate target object, detected by an image sensor, according to a first predetermined motion model, and to determine a distribution of the first information, (2) a second target object tracking unit including a second processor, configured to correct a second information of at least one second candidate target object, detected by an active type sensor, according to a second predetermined motion model, and to determine a distribution of the second information, (3) a matching unit configured to obtain a plurality of distribution parameters based on a correlation of the distributions of the first and second information, and (4) a false image determining unit configured to determine whether or not the second information corresponds to a false image based on the plurality of distribution parameters.

Abstract: It is possible to improve estimation accuracy with regard to data in which significance is attached to a relative phase. Provided is an information processing device including an estimation unit configured to estimate a status by using a neural network. The neural network includes a first complex-valued neural network to which complex data is input, a phase difference computation layer from which phase difference for each element between a plurality of sets with regard to the complex data is output, and a second complex-valued neural network from which complex data is output on the basis of the phase difference.

Abstract: Provided is a state recognizing device including: a first filter unit performing a filtering process on a time-series signal obtained by performing remote measuring on a space, in accordance with a first cutoff frequency to allow a signal component deriving from movement of a biological organism to pass through; a second filter unit performing a filtering process on the time-series signal in accordance with a second cutoff frequency to allow a signal component based on biological information to pass through; an amplitude-component extracting unit extracting a first feature quantity related to an amplitude component from a signal passed through the first and/or second filter units; a frequency-component extracting unit extracting a second feature quantity related to a frequency component from a signal passed through the first and/or second filter units; and a recognizing unit recognizing a state of the space by using the first and second feature quantities.

Abstract: To reduce a network size and calculation cost with regard to a neural network to which multidimensional data is input. Provided is an information processing device including: an estimation unit configured to estimate a status by using a neural network constituted by single- or multi-dimensional neurons that perform output on the basis of input multidimensional data. The neural network includes a transformation layer configured to transform output of a type 1 neuron into a dimension corresponding to input of a type 2 neuron, and the type 2 neuron performs a process based on lower-dimensional data than the type 1 neuron.

Abstract: A tracking apparatus, including (1) a first target object tracking unit having a first processor, configured to correct a first information of at least one first candidate target object, detected by an image sensor, according to a first predetermined motion model, and to determine a distribution of the first information, (2) a second target object tracking unit including a second processor, configured to correct a second information of at least one second candidate target object, detected by an active type sensor, according to a second predetermined motion model, and to determine a distribution of the second information, (3) a matching unit configured to obtain a plurality of distribution parameters based on a correlation of the distributions of the first and second information, and (4) a false image determining unit configured to determine whether or not the second information corresponds to a false image based on the plurality of distribution parameters.

Abstract: To improve the accuracy of the determination on whether or not a moving object is present in a predetermined region, a control device for use in a system configured to conduct presence-or-absence determination on whether or not a moving object is present on the basis of detection by a first sensor provided in a predetermined compartment region, the control device comprising: a mode control section configured to control switching of an operation mode for the detection by the first sensor or the presence-or-absence determination; and an acquisition section configured to acquire a determination result of whether or not a moving object is present in an adjacent region adjacent to the predetermined compartment region and not including the predetermined compartment region; wherein the mode control section controls the switching of the operation mode in response to the determination result acquired by the acquisition section, is provided.

Abstract: An estimation device includes a first converting unit configured to convert a beat signal to a one-dimensional first candidate signal on the basis of a two-dimensional distribution of the beat signal, a second converting unit configured to convert the beat signal to a one-dimensional second candidate signal on the basis of a two-dimensional position change of the beat signal, and a signal deciding unit configured to decide a one-dimensional signal on the basis of the first candidate signal and the second candidate signal.

Abstract: There is provided a period estimation apparatus including: a first frequency estimation unit that estimates a first frequency of a one-dimensional signal on the basis of a phase difference between the one-dimensional signal and a reference signal and a temporal change in the phase difference; and a second frequency estimation unit that estimates a second frequency of the one-dimensional signal by cutting out a comparative signal having a section length equivalent to a first period corresponding to the first frequency from the one-dimensional signal, and calculating a correlation coefficient between the comparative signal and the one-dimensional signal having the section length.

Abstract: There is provided a state determination device including: an acquisition unit configured to acquire information indicating a kinetic state of a moving object existing in a target space; a setting unit configured to set a plurality of subspaces in the space; a storage unit configured to store statistical information of kinetic states of the moving object acquired by the acquisition unit from the respective subspaces set by the setting unit; a model estimation unit configured to estimate a kinetic model of the moving object on the basis of the statistical information stored in the storage unit; and a determination unit configured to determine a state of the moving object by comparing the kinetic states of the moving object acquired by the acquisition unit with the kinetic model estimated by the model estimation unit.

Abstract: [Object] To provide a characteristic-value calculating device, a characteristic-value calculating method, and a recording medium that can extract a characteristic value for more accurately recognizing the state of a moving object, such as a human, from a Doppler signal. [Solution] A characteristic-value calculating device includes an acquiring unit that acquires a Doppler signal, an extracting unit that extracts a time-series signal constituted of a predetermined frequency component from the Doppler signal acquired by the acquiring unit, a selecting unit that selects a signal value at a predetermined interval from the time-series signal extracted by the extracting unit, and a calculating unit that calculates higher-order local autocorrelation based on the signal value selected by the selecting unit.

Abstract: Provided is a state recognizing device including: a first filter unit performing a filtering process on a time-series signal obtained by performing remote measuring on a space, in accordance with a first cutoff frequency to allow a signal component deriving from movement of a biological organism to pass through; a second filter unit performing a filtering process on the time-series signal in accordance with a second cutoff frequency to allow a signal component based on biological information to pass through; an amplitude-component extracting unit extracting a first feature quantity related to an amplitude component from a signal passed through the first and/or second filter units; a frequency-component extracting unit extracting a second feature quantity related to a frequency component from a signal passed through the first and/or second filter units; and a recognizing unit recognizing a state of the space by using the first and second feature quantities.

Abstract: The invention provides an object detection device including a statistical model estimation section that, using a Doppler signal in a specific period of time for a given reflecting object, or using data obtained by performing a specific data conversion on the Doppler signal, estimates a statistical model expressing time series fluctuations in the Doppler signal or in the data, and a determination section that determines whether or not there is an aperiodically moving object present at the reflecting object based on incompatibility between the statistical model estimated by the statistical model estimation section and time series fluctuations in the Doppler signal or in the data.

Abstract: To improve the accuracy of the determination on whether or not a moving object is present in a predetermined region, a control device for use in a system configured to conduct presence-or-absence determination on whether or not a moving object is present on the basis of detection by a first sensor provided in a predetermined compartment region, the control device comprising: a mode control section configured to control switching of an operation mode for the detection by the first sensor or the presence-or-absence determination; and an acquisition section configured to acquire a determination result of whether or not a moving object is present in an adjacent region adjacent to the predetermined compartment region and not including the predetermined compartment region; wherein the mode control section controls the switching of the operation mode in response to the determination result acquired by the acquisition section, is provided.

Abstract: There is provided an information processing apparatus including: an input unit inputting first vibration information observed from a moving body; a generating unit generating second vibration information based on a periodic function including at least one parameter that models periodic motion of the moving body; and an estimating unit estimating the at least one parameter based on a comparison result for the first vibration information inputted by the input unit and the second vibration information generated by the generating unit. The estimating unit repeatedly estimates the at least one parameter based on a comparison result for the first vibration information and the second vibration information that has been regenerated by the generating unit using the estimated at least one parameter.