A method of estimating weight of food objects, includes training an artificial neural network software module, and using the trained artificial neural network software module to provide a weight correlated data estimate for said food object based on a three-dimensional image of the food object

A method of estimating weight of food objects, includes training an artificial neural network software module, and using the trained artificial neural network software module to provide a weight correlated data estimate for said food object based on a three-dimensional image of the food object

A computer-implemented method of using interferometry to detect mass changes of objects in a solution includes obtaining a time series of images using interferometry, and performing background correction on each image by classifying pixels of the image as background pixels or object pixels, fitting only the background pixels of the image to a function to generate a background fitted function, and subtracting the background fitted function from the image to generate a background corrected image. The method includes performing segmentation on the background corrected images to resolve boundaries of one or more objects, performing motion tracking on the objects to track changes in position of the objects, determining respective masses of the motion tracked objects and determining, for each image in the time series, an aggregate mass based on the respective masses to determine whether the aggregate mass of the motion tracked objects is increasing or decreasing.

A computer-implemented method of using interferometry to detect mass changes of objects in a solution includes obtaining a time series of images using interferometry, and performing background correction on each image by classifying pixels of the image as background pixels or object pixels, fitting only the background pixels of the image to a function to generate a background fitted function, and subtracting the background fitted function from the image to generate a background corrected image. The method includes performing segmentation on the background corrected images to resolve boundaries of one or more objects, performing motion tracking on the objects to track changes in position of the objects, determining respective masses of the motion tracked objects and determining, for each image in the time series, an aggregate mass based on the respective masses to determine whether the aggregate mass of the motion tracked objects is increasing or decreasing.

A body weight estimation device includes: a data reception unit that receives gait data including the gait characteristics of a walking person; a first calculation unit that extracts a feature quantity based on the gait characteristics of the walking person from the gait data; a second calculation unit that generates a learning model by learning a correlation between the feature quantity extracted by the first calculation unit and body weight information about the walking person, using the gait data as sample data; and an estimation unit that estimates the body weight information associated with the gait data of an estimation target by inputting the gait data of the estimation target to the learning model.

The invention resides in a method or system configured to estimate the mass of material in a stockpile. The surface profile of the stockpile is obtained and a plurality of layers are defined in the stockpile. Each layer extends parallel to the surface profile. Density characteristics of the stockpile material are obtained, from database records or measurement tests. The volume of each layer is estimated. The density of each layer is estimated, according to the density characteristics of the stockpile material. Using the volume of each layer and the density of each layer the mass of the stockpile is calculated.

Assisted racking of digital resistance includes detecting a state of a cable. A motor is mechanically coupled to the cable to provide resistance during an exercise by tensioning the cable. It further includes determining completion of the exercise based at least in part on the detected state of the cable. It further includes selectively removing resistance from the cable based at least in part on the determination that the user has completed the exercise.

A sheet property measurement device includes: an insertion portion into which a sheet to be inserted; a reading sensor configured to read a surface of the sheet inserted into the insertion portion; and a controller. The controller is configured to: measure a property of the surface of the sheet based on a plurality of reading results given by the reading sensor; and output a measurement error in a case where all the plurality of reading results given by the reading sensor do not change from a reading result given at one location on the surface of the sheet in an insertion direction of inserting the sheet.

A sheet property measurement device includes: an insertion portion into which a sheet to be inserted; a reading sensor configured to read a surface of the sheet inserted into the insertion portion; and a controller. The controller is configured to: measure a property of the surface of the sheet based on a plurality of reading results given by the reading sensor; and output a measurement error in a case where all the plurality of reading results given by the reading sensor do not change from a reading result given at one location on the surface of the sheet in an insertion direction of inserting the sheet.

Provided are a porosity deriving method and a porosity deriving device capable of deriving a porosity of an inspection object being conveyed. The porosity deriving method of deriving a porosity of the inspection object includes: a basis weight measuring step including measuring a basis weight of a specific part of the inspection object being conveyed; a thickness measuring step including measuring a thickness of the specific part of the inspection object being conveyed; and a porosity deriving step including deriving a porosity of the inspection object from the basis weight, the thickness, and a true density of the inspection object.