Abstract: [Problem] Provided is a novel information processing technology relating to a predetermined object in an image. [Solving Means] An information processing apparatus includes: an image acquisition unit that acquires an image used as teacher data for machine learning, the image being with one or a plurality of annotations for showing a position in the image at which a predetermined object is shown; an adjustment image generation unit that generates an adjustment image in which parameters of the image are adjusted; and a machine learning unit that generates a learning model for detecting the predetermined object in an image by performing machine learning using teacher data including the adjustment image.

Abstract: An information processing apparatus includes: a generating unit configured to generate, from a data group including training data elements given different correct labels, multiple training data sets in such a manner that the number of included training data elements changes successively, by successively selecting one or more training data elements from the data group; and a training unit configured to repeatedly train a learning model for machine learning by applying the training data sets to the learning model.

Abstract: [Problem] Provided is a novel information processing technology relating to a predetermined object in an image. [Solving Means] An information processing apparatus includes: an image acquisition unit that acquires an image used as teacher data for machine learning, the image being with one or a plurality of annotations for showing a position in the image at which a predetermined object is shown; a region specification unit that specifies a region in which the one or the plurality of annotations satisfy a predetermined criterion in the image; an edge detection unit that preferentially detects edges in the specified region or a range set on a basis of the region; and an annotation correction unit that corrects the annotations so as to be along the detected edges.

Abstract: An information processing apparatus having a first fitness calculation to calculate a fitness using a predetermined function for models in a population; a virtual model generating to select, as parent models, models having higher value of the fitness using the first fitness calculation among the models, and generate a virtual model that outputs by performing calculation of output results of the selected parent models; a second fitness calculation to calculate the fitness of the virtual model using the predetermined function; a replacing operation constituting the population by adding the virtual model and by deleting a model having lower value of the fitness among the models in the population; and a model extracting to extract a model having higher value of the fitness from the population by repeating processing by the virtual model generating, the second fitness calculation, and the model replacing until a predetermined termination condition is reached.

Abstract: An input data generation unit is configured to generate, based on log data indicating a log of a behavior of a user with respect to a given computer resource for each period, input data for the period, which is associated with the log data. A user probability data generation unit is configured to generate user probability data based on output obtained from a trained machine learning model when the input data is input to the trained machine learning model. An anomaly determination unit is configured to determine whether an anomaly has occurred in the behavior of the user during a latest period based on the user probability data generated based on the input data for the latest period and the user probability data generated based on the input data for a period before the latest period.

Abstract: An information processing apparatus includes a first fitness calculation unit for calculating a fitness using a predetermined function for each of a plurality of models belonging to a population; a virtual model generating unit for selecting, as parent models, a plurality of models having higher value of the fitness among the plurality of models, and generating a virtual model that outputs an output result obtained by performing calculation of output results of the selected plurality of parent models; a second fitness calculation unit for calculating the fitness of the virtual model using the predetermined function; a model replacing unit for replacing the models constituting the population by adding the virtual model to the population and by deleting a model having a lower value of the fitness from the population; and a model extracting unit for extracting a model having a higher value of the fitness from the population.