There is provided a method, comprising: feeding 2D image(s) of an internal surface of a colon captured by an endoscopic camera, into a machine learning model, wherein the 2D image(s) excludes a depiction of an external measurement tool, wherein the machine learning model is trained on records, each including 2D images of the internal surface of the colon of a respective subject labelled with ground truth labels of respective bounding boxes enclosing respective polyps and at least one of an indication of size and a type of the respective polyp indicating likelihood of developing maligiancy, obtaining a bounding box for a polyp and at least one of an indication of size and type of the polyp, and generating instructions for presenting within the GUI, an overlay of the bounding box over the polyp and the at least one of the indication of size and type of the polyp.

There is provided a method, comprising: feeding 2D image(s) of an internal surface of a colon captured by an endoscopic camera, into a machine learning model, wherein the 2D image(s) excludes a depiction of an external measurement tool, wherein the machine learning model is trained on records, each including 2D images of the internal surface of the colon of a respective subject labelled with ground truth labels of respective bounding boxes enclosing respective polyps and at least one of an indication of size and a type of the respective polyp indicating likelihood of developing maligiancy, obtaining a bounding box for a polyp and at least one of an indication of size and type of the polyp, and generating instructions for presenting within the GUI, an overlay of the bounding box over the polyp and the at least one of the indication of size and type of the polyp.

When three-dimensional audio is produced by using headphones, particular HRTF-filters are used to modify sound for the left and right channels of the headphone. As the morphology of every ear is different, it is beneficial to have HRTF-filters particularly designed for the user of headphones. Such filters may be produced by deriving ear geometry from a plurality of images taken with an ordinary camera, detecting necessary features from images and fitting said features to a model that has been produced from accurately scanned ears comprising representative values for different sizes and shapes. Taken images are sent to a server (52) that performs the necessary computations and submits the data further or produces the requested filter.

When three-dimensional audio is produced by using headphones, particular HRTF-filters are used to modify sound for the left and right channels of the headphone. As the morphology of every ear is different, it is beneficial to have HRTF-filters particularly designed for the user of headphones. Such filters may be produced by deriving ear geometry from a plurality of images taken with an ordinary camera, detecting necessary features from images and fitting said features to a model that has been produced from accurately scanned ears comprising representative values for different sizes and shapes. Taken images are sent to a server (52) that performs the necessary computations and submits the data further or produces the requested filter.

One embodiment provides a method, including: obtaining at least one video capturing images of a writing capture device used during a business process design session, wherein the images comprise portions of the process flow; obtaining at least one audio recording corresponding to the business process design session; identifying an intended business process model shape; determining at least one business process model shape missing from the process flow provided on the writing capture device; identifying a task dependency for pairs of business process model shapes; and generating a business process model from (i) the intended business process model shapes, (ii) the at least one business process model shape missing from the process flow, and (iii) the identified task dependencies.

One embodiment provides a method, including: obtaining at least one video capturing images of a writing capture device used during a business process design session, wherein the images comprise portions of the process flow; obtaining at least one audio recording corresponding to the business process design session; identifying an intended business process model shape; determining at least one business process model shape missing from the process flow provided on the writing capture device; identifying a task dependency for pairs of business process model shapes; and generating a business process model from (i) the intended business process model shapes, (ii) the at least one business process model shape missing from the process flow, and (iii) the identified task dependencies.

Various aspects of a system and a method for determining a position of one or more multi-dimensional objects are disclosed herein. In accordance with an embodiment, the system may include a memory and a processor. The processor may be configured to obtain, from a plurality of satellite images, shadow data of a first multi-dimensional object from one or more multi-dimensional objects on a visible surface. The processor may be configured to obtain, from a server, base elevation data and height data of the first multi-dimensional object. The processor may be further configured to generate a Digital Elevation Model (DEM) of the plurality of multi-dimensional objects. The processor may be further configured to determine a position of a second multi-dimensional object of the plurality of multi-dimensional objects on the visible surface, based on the generated DEM.

Various aspects of a system and a method for determining a position of one or more multi-dimensional objects are disclosed herein. In accordance with an embodiment, the system may include a memory and a processor. The processor may be configured to obtain, from a plurality of satellite images, shadow data of a first multi-dimensional object from one or more multi-dimensional objects on a visible surface. The processor may be configured to obtain, from a server, base elevation data and height data of the first multi-dimensional object. The processor may be further configured to generate a Digital Elevation Model (DEM) of the plurality of multi-dimensional objects. The processor may be further configured to determine a position of a second multi-dimensional object of the plurality of multi-dimensional objects on the visible surface, based on the generated DEM.

An apparatus for optical inspection of sanitaryware includes: a supporting device configured to receive a piece of sanitaryware to be inspected; at least one camera, configured to capture a plurality of images of the piece of sanitaryware under inspection; an automatic arm, movable between a plurality of operating positions relative to the supporting device, wherein the at least one camera is mounted on the automatic arm; a control unit, configured to receive the plurality of images, wherein the control unit is configured to process the plurality of images as a function of reference data to provide diagnostic information regarding the defectiveness of the piece of sanitaryware.

An apparatus for optical inspection of sanitaryware includes: a supporting device configured to receive a piece of sanitaryware to be inspected; at least one camera, configured to capture a plurality of images of the piece of sanitaryware under inspection; an automatic arm, movable between a plurality of operating positions relative to the supporting device, wherein the at least one camera is mounted on the automatic arm; a control unit, configured to receive the plurality of images, wherein the control unit is configured to process the plurality of images as a function of reference data to provide diagnostic information regarding the defectiveness of the piece of sanitaryware.