An information processing system creates a teacher database configured to train an analysis model from an observation image and labeling information corresponding to the observation image using an information processor. This system includes a storage unit, an image processing unit, and a teacher database creating unit. The storage unit stores image processing data formed of information showing a relationship between an observation condition and a parameter relating to the observation image. Further stores a first observation image, a first observation condition, and first labeling information. The image processing unit accepts the first observation image and the first observation condition as inputs, performs image processing corresponding to the parameter to the first observation image based on the image processing data, and creates a second observation image corresponding to a second observation condition. The teacher database creating unit creates the teacher database from the second observation image and the first labeling information.

Embodiments of the present disclosure provide an image classification method for a computer device. The method includes obtaining an original image and a category of an object included in the original image; adjusting a display parameter of the original image to satisfy a value condition to obtain an adjusted original image; and transforming the display parameter of the original image according to a distribution condition that distribution of the display parameter needs to satisfy, to obtain a transformed image. The method also includes training a neural network model based on the category of the object and a training set constructed by the adjusted original image and the transformed image; and determining a category of an object included in a to-be-predicted image based on the trained neural network model.

Monitoring a processing asset for one of an oil processing facility and a gas processing facility includes a data acquisition circuit structured to interpret a plurality of detection values corresponding to input received from a detection package, the detection package comprising at least one of a plurality of input sensors, each of the plurality of input sensors operatively coupled to at least one of a plurality of process components; a data analysis circuit structured to analyze a subset of the plurality of detection values to determine a status parameter; and an analysis response circuit structured to adjust a process utilizing the processing asset in response to the status parameter comprising altering at least one process parameter selected from the process parameters consisting of: a temperature, an operating speed, a utilization value of one of the plurality of process components, and a process flow.

The present disclosure relates to systems and methods for generating headshots from a plurality of still images. In one implementation, the system may include a memory storing instructions and a processor configured to execute the instructions. The instructions may include instructions to receive a plurality of still images from one or more video feeds, score the plurality of images along a plurality of dimensions based on a scale, rank the plurality of images using at least one of a composite score or at least one of the dimensions, select a subset of the plurality of images using the ranking, and construct at least one headshot of the user from the subset of the plurality of images.

Various embodiments of the present disclosure relate to an electronic device and a feedback information acquisition method therefor. The feedback information acquisition method of the electronic device includes: acquiring input feedback information of a user and first response information of the user, which are related to a specific function; training a feedback estimation model by using the input feedback information and the first response information; acquiring second response information of the user related to the specific function; and acquiring feedback information related to the specific function by applying the second response information to the trained feedback estimation model.

Computer systems and associated methods are disclosed to implement a model development environment (MDE) that allows a team of users to perform iterative model experiments to develop machine learning (ML) media models. In embodiments, the MDE implements a media data management interface that allows users to annotate and manage training data for models. In embodiments, the MDE implements a model experimentation interface that allows users to configure and run model experiments, which include a training run and a test run of a model. In embodiments, the MDE implements a model diagnosis interface that displays the model's performance metrics and allows users to visually inspect media samples that were used during the model experiment to determine corrective actions to improve model performance for later iterations of experiments. In embodiments, the MDE allows different types of users to collaborate on a series of model experiments to build an optimal media model.

A system includes a sensor and a remote processing and storage component in communication with the sensor. The sensor generates sensor data indicative of the presence of people or objects in a scene. The remote processing and storage component receives the sensor data from the sensor and performs an automated counting process to determine an automated count of people or objects. The component receives a request to perform a validation process for the sensor. The component also generates and transmits a link to a manual validation page that includes an interface for performing a manual count. The component further receives an indication to start a validation process from the manual validation page, generates an automated count value from the performed automated counting process, and receives manual count data. The component also generates a validation report based on the automated count value and the manual count data.

Vehicle navigation control systems in autonomous driving rely on accurate predictions of objects within the vicinity of the vehicle to appropriately control the vehicle safely through its surrounding environment. Accordingly this disclosure provides methods and devices which implement mechanisms for obtaining contextual variables of the vehicle's environment for use in determining the accuracy of predictions of objects within the vehicle's environment.

A non-transitory recording medium stores a program causing a computer to execute a process including determining a reference value on a decision surface classifying a group of image data represented by a plurality of types of feature quantities into two classes in a feature quantity space, based on a feature quantity of given image data that is closest to the decision surface and is classified into one of the classes of the group of image data in the feature quantity space, plotting and displaying pieces of image data of the group of image data along at least one axis indicating a degree of separation of each of the pieces of image data relative to the reference value, modifying, upon receiving a single piece of image data identified from the plotted and displayed pieces of image data, the decision surface based on the identified single piece of image data.

Methods, system and apparatus for monitoring vibration sensitive industrial equipment is disclosed. The system may include a data acquisition circuit structured to interpret a plurality of detection values, each of the plurality of detection values corresponding to input received from at least one of a plurality of input sensors, each of the plurality of input sensors operatively coupled to at least one of a plurality of components of the equipment, a signal conditioning circuit structured to process a subset of the detection values on multiples of a key frequency, a vibration analysis circuit structured to identify vibration in at least one of the plurality of components, a data analysis circuit structured to analyze the plurality of detection values and determine a status parameter value, and an analysis response circuit structured to take an action in response to the status parameter value.