Abstract: The present invention generally relates to a method, a system and a computer program for shape optimisation of a technical device adapted to be exposed to a fluid flowing around a contour of said device with respect to its fluid dynamic parameters. In order to provide an improved method for shape optimisation of a technical device with respect to its fluid dynamic parameters which is faster, a method is provided comprising discretizing the shape of the technical device into a plurality of points along the contour of the technical device or into a surface mesh, and inputting the plurality of points or the surface mesh into a Convolutional Neural Network (CNN) for computing a prediction of the at least one fluid dynamic parameter.

Abstract: An automated method for manufacturing objects, the method using an image capturing device and a data processing device for quality inspection, wherein the method includes a learning phase and a manufacturing phase for manufacturing the objects, wherein the learning phase comprises producing N objects considered to be acceptable; taking at least one reference primary image of each of the N objects; dividing each reference primary image into (Pk) reference secondary images (Sk,p), grouping the corresponding reference secondary images into batches of N images, and determining a compression-decompression model (Fk,p) with a compression factor (Qk,p) per batch.

Abstract: A process for continuous welding of a sheet of plastic material for manufacturing flexible packages, comprising a step of positioning the sheet relative to the welding device, putting ends of the sheet into contact, forming a weld by heating, pressing and cooling the ends of the sheet that are in contact, acquiring a primary temporal signal with a sensor, the primary temporal signal proportional to a thickness of the weld, transforming the primary temporal signal into a primary frequency signal and defining a low-frequency spectrum, a medium-frequency spectrum, and a high-frequency spectrum from the primary frequency signal, reconstructing a secondary low-frequency signal from the low-frequency spectrum, and determining the thickness of the weld based on the secondary low-frequency signal.

Abstract: A process for continuous welding of a sheet of plastic material for manufacturing flexible packages, comprising a step of positioning the sheet relative to the welding device, putting ends of the sheet into contact, forming a weld by heating, pressing and cooling the ends of the sheet that are in contact, acquiring a primary temporal signal with a sensor, the primary temporal signal proportional to a thickness of the weld, transforming the primary temporal signal into a primary frequency signal and defining a low-frequency spectrum, a medium-frequency spectrum, and a high-frequency spectrum from the primary frequency signal, reconstructing a secondary low-frequency signal from the low-frequency spectrum, and determining the thickness of the weld based on the secondary low-frequency signal.

Abstract: The present invention generally relates to a method, a system and a computer program for shape optimisation of a technical device adapted to be exposed to a fluid flowing around a contour of said device with respect to its fluid dynamic parameters. In order to provide an improved method for shape optimisation of a technical device with respect to its fluid dynamic parameters which is faster, a method is provided comprising discretizing the shape of the technical device into a plurality of points along the contour of the technical device or into a surface mesh, and inputting the plurality of points or the surface mesh into a Convolutional Neural Network (CNN) for computing a prediction of the at least one fluid dynamic parameter.

Abstract: Method for orienting tube components (2), such as heads or stoppers, comprising a step of measuring the angular position (6) of a component followed by a step of orienting said component, in which step the angular correction of the component is determined especially while taking into account the measured signal (8); method characterized in that said angular correction is also determined while taking into account a modelled parasitic signal (15). The invention also comprises a device using said method.

Abstract: Method for orienting tube components (2), such as heads or stoppers, comprising a step of measuring the angular position (6) of a component followed by a step of orienting said component, in which step the angular correction of the component is determined especially while taking into account the measured signal (8); method characterized in that said angular correction is also determined while taking into account a modelled parasitic signal (15). The invention also comprises a device using said method.

Abstract: Systems and methods for tracking interacting objects may acquire, with a sensor, and two or more images associated with two or more time instances. A processor may generate image data from the two or more images. The processor may apply an extended Probability Occupancy Map (POM) algorithm to the image data to obtain probability of occupancy for a container class of potentially interacting objects, probability of occupancy for a containee class of the potentially interacting objects, and a size relationship of the potentially interacting objects, over a set of discrete locations on a ground plane for each time instance. The processor may estimate trajectories of an object belonging to each of the two classes by determining a solution of a tracking model on the basis of the occupancy probabilities and a set of rules describing the interaction between objects of different or the same classes.

Abstract: Systems and methods for tracking interacting objects may acquire, with a sensor, and two or more images associated with two or more time instances. A processor may generate image data from the two or more images. The processor may apply an extended Probability Occupancy Map (POM) algorithm to the image data to obtain probability of occupancy for a container class of potentially interacting objects, probability of occupancy for a containee class of the potentially interacting objects, and a size relationship of the potentially interacting objects, over a set of discrete locations on a ground plane for each time instance. The processor may estimate trajectories of an object belonging to each of the two classes by determining a solution of a tracking model on the basis of the occupancy probabilities and a set of rules describing the interaction between objects of different or the same classes.

Abstract: Object detection receives an input image to detect an object of interest. It determines feature matrices based on the received image, wherein each matrix represents a feature of the received image. The plurality of matrices are Fourier transformed to Fourier feature matrices. Fourier filter matrices are provided, each representing a feature of an object transformed in Fourier space. Each filter matrix is point-wise multiplied with one of the feature matrices corresponding to the same feature. The plurality of matrices are summed, resulting by point-wise multiplying each Fourier filter matrix with the corresponding Fourier feature matrix to obtain a Fourier score matrix. An inverse Fourier transform of the Fourier score matrix is performed, resulting in a score matrix, which is used to detect the object in the input image.

Abstract: Object detection receives an input image to detect an object of interest. It determines feature matrices based on the received image, wherein each matrix represents a feature of the received image. The plurality of matrices are Fourier transformed to Fourier feature matrices. Fourier filter matrices are provided, each representing a feature of an object transformed in Fourier space. Each filter matrix is point-wise multiplied with one of the feature matrices corresponding to the same feature. The plurality of matrices are summed, resulting by point-wise multiplying each Fourier filter matrix with the corresponding Fourier feature matrix to obtain a Fourier score matrix. An inverse Fourier transform of the Fourier score matrix is performed, resulting in a score matrix, which is used to detect the object in the input image.

Abstract: Trajectories of objects are estimated by determining the optimal solution(s) of a tracking model on the basis of an occupancy probability distribution. The occupancy probability distribution is the probability of presence of objects over a set of discrete points in the spatio-temporal space at a number of time steps. The tracking model is defined by the set of discrete points, a virtual source location and a virtual sink location, wherein objects in the tracking model are creatable in the virtual source location and are removable in the virtual sink location.

Abstract: Trajectories of objects are estimated by determining the optimal solution(s) of a tracking model on the basis of an occupancy probability distribution. The occupancy probability distribution is the probability of presence of objects over a set of discrete points in the spatio-temporal space at a number of time steps. The tracking model is defined by the set of discrete points, a virtual source location and a virtual sink location, wherein objects in the tracking model are creatable in the virtual source location and are removable in the virtual sink location.