A method for calibrating an induction cooking device includes capturing image data representing a cooking vessel and processing the image data to identify one or more features. The method further includes comparing the image data representing the cooking vessel to a library of stored image data of calibrated cookware. In response to identifying stored image data in the library that matches the one or more features, the method accesses preconfigured calibration data and configures the operation of the induction cooking device based on the preconfigured calibration data.

In various embodiments, a method includes receiving a data set including one or more data points; determining a layout based on an image, the layout including one or more locations in the image; generating a visualization including the image and one or more visual elements, wherein each visual element indicates at least one data point of the data set, and each visual element is located in the visualization at a location of the one or more locations of the layout based on the at least one data point indicated by the visual element; and displaying the visualization.

In various embodiments, a method includes receiving a data set including one or more data points; determining a layout based on an image, the layout including one or more locations in the image; generating a visualization including the image and one or more visual elements, wherein each visual element indicates at least one data point of the data set, and each visual element is located in the visualization at a location of the one or more locations of the layout based on the at least one data point indicated by the visual element; and displaying the visualization.

Provided is a process including: receiving inspection path information indicating a path for a robot to travel, and a plurality of locations along the path to inspect; determining, based on information received via a location sensor, that a distance between a location of the robot and a first location of the plurality of locations is greater than a threshold distance; in response, causing a refrigeration system of an optical gas imaging (OGI) camera to decrease cooling; moving along the path; in response to determining that the robot is at a first location of the plurality of locations, sending a second command to the sensor system, wherein the second command causes the refrigeration system of the OGI camera to increase cooling; causing the sensor system to record a first video with an OGI camera; and causing the sensor system to store the first video in memory.

Embodiments of the present invention provide systems, methods, and non-transitory computer storage media for parsing a given input referring expression into a parse structure and generating a semantic computation graph to identify semantic relationships among and between objects. At a high level, when embodiments of the preset invention receive a referring expression, a parse tree is created and mapped into a hierarchical subject, predicate, object graph structure that labeled noun objects in the referring expression, the attributes of the labeled noun objects, and predicate relationships (e.g., verb actions or spatial propositions) between the labeled objects. Embodiments of the present invention then transform the subject, predicate, object graph structure into a semantic computation graph that may be recursively traversed and interpreted to determine how noun objects, their attributes and modifiers, and interrelationships are provided to downstream image editing, searching, or caption indexing tasks.

Embodiments of the present invention provide systems, methods, and non-transitory computer storage media for parsing a given input referring expression into a parse structure and generating a semantic computation graph to identify semantic relationships among and between objects. At a high level, when embodiments of the preset invention receive a referring expression, a parse tree is created and mapped into a hierarchical subject, predicate, object graph structure that labeled noun objects in the referring expression, the attributes of the labeled noun objects, and predicate relationships (e.g., verb actions or spatial propositions) between the labeled objects. Embodiments of the present invention then transform the subject, predicate, object graph structure into a semantic computation graph that may be recursively traversed and interpreted to determine how noun objects, their attributes and modifiers, and interrelationships are provided to downstream image editing, searching, or caption indexing tasks.

Provided is a method and processing unit for computer-implemented analysis of a classification model which is adapted to map, as a prediction, a number of input instances, each of them having a number n of features, into a number of probabilities of output classes, as a classification decision, according to a predetermined function, and which is adapted to determine a relevance value for each feature resulting in a saliency map. The disclosure includes the step of identifying an effect of each feature on the prediction of the instance by determining, for each feature, a relevance information representing a contextual information for all features of the instance omitting the considered feature. Then, the relevance value for each feature is determined. Finally, the plurality of relevance values for the features of the instance is evaluated to identify the effect of each feature on the prediction of the instance.

Provided is a method and processing unit for computer-implemented analysis of a classification model which is adapted to map, as a prediction, a number of input instances, each of them having a number n of features, into a number of probabilities of output classes, as a classification decision, according to a predetermined function, and which is adapted to determine a relevance value for each feature resulting in a saliency map. The disclosure includes the step of identifying an effect of each feature on the prediction of the instance by determining, for each feature, a relevance information representing a contextual information for all features of the instance omitting the considered feature. Then, the relevance value for each feature is determined. Finally, the plurality of relevance values for the features of the instance is evaluated to identify the effect of each feature on the prediction of the instance.

The present invention provides an automatic system for visual guidance and navigation using real-time visual anchor point detection, which includes an edge device, a cloud device, and a landmark database; the system of the present invention provides users with navigation directions via visual landmarks. A candidate visual landmark image is selected from the database; the system of the present invention can calculate the time of day, the current weather condition, the current season, etc. In addition, the system of the present invention can use the camera on the dashboard of the vehicle, the camera in the smartphone, or other cameras to collect real-time images; the system of the present invention can also provide feedback on the visibility or salience of landmarks to improve the visual landmark images obtained by subsequent users.

The present invention provides an automatic system for visual guidance and navigation using real-time visual anchor point detection, which includes an edge device, a cloud device, and a landmark database; the system of the present invention provides users with navigation directions via visual landmarks. A candidate visual landmark image is selected from the database; the system of the present invention can calculate the time of day, the current weather condition, the current season, etc. In addition, the system of the present invention can use the camera on the dashboard of the vehicle, the camera in the smartphone, or other cameras to collect real-time images; the system of the present invention can also provide feedback on the visibility or salience of landmarks to improve the visual landmark images obtained by subsequent users.