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.

Provided is a technique which makes it possible to suitably evaluate a weight of a target object disposed in a container. A weight estimation method includes: a first obtaining step of obtaining first image data for training included in first type image data on a target object which has been scooped up by an excavator and is disposed in a container; a training step of training, with reference to the first image data and a measured weight of the target object, an estimation model that outputs a weight of the target object based on the first type image data; a second obtaining step of obtaining second image data for estimation included in the first type image data; and an estimating step of estimating the weight of the target object based on the estimation model and the second image data.

Provided is a technique which makes it possible to suitably evaluate a weight of a target object disposed in a container. A weight estimation method includes: a first obtaining step of obtaining first image data for training included in first type image data on a target object which has been scooped up by an excavator and is disposed in a container; a training step of training, with reference to the first image data and a measured weight of the target object, an estimation model that outputs a weight of the target object based on the first type image data; a second obtaining step of obtaining second image data for estimation included in the first type image data; and an estimating step of estimating the weight of the target object based on the estimation model and the second image data.

An axle load measuring apparatus includes a displacement calculator, a storage, and an axle load calculator. The displacement calculator detects displacements of positions on a road caused by an axle load using a captured image of the road and a vehicle thereon. When a certain amount of load is applied to a predetermined position of the road, the storage stores a displacement function representing shape information of a spatial distribution of a displacement of the road originated from the predetermined position. The axle load calculator calculates the axle load based on the displacements of the positions and the displacement function.

An axle load measuring apparatus includes a displacement calculator, a storage, and an axle load calculator. The displacement calculator detects displacements of positions on a road caused by an axle load using a captured image of the road and a vehicle thereon. When a certain amount of load is applied to a predetermined position of the road, the storage stores a displacement function representing shape information of a spatial distribution of a displacement of the road originated from the predetermined position. The axle load calculator calculates the axle load based on the displacements of the positions and the displacement function.

A fill level measurement device for determining a topology of a filling material surface is provided, including an antenna apparatus including an array of radiator elements and a rotatable mount configured to rotate the antenna apparatus about an axis that is in parallel with the array, such that a plurality of emission angles of the antenna apparatus are electronically and mechanically settable relative to the filling material surface without local overscanning occurring.

The invention relates to a method for ascertaining a net weight of a product in a product range, plurality of contiguous product ranges form a product chain and a total weight of the product chain is ascertained. The product chain is X-rayed to ascertain values that correspond to the radiation that penetrates a defined range of the product chain. The ascertained values are used to ascertain a total value for the entire product chain. A product range with a single product is selected by means of evaluation of the ascertained values. A value of the product range is formed from the ascertained values. A gross weight of the product range is ascertained therefrom. The net weight used for the single product is approximately the weight or the net weight is ascertained from the difference between the weight and a prescribed or ascertained weight of the product range without a product.

A load meter includes a detector, a storage unit, and a load calculator. The detector detects, by using a captured image obtained by capturing a road and a vehicle present on the road, a displacement amount in the captured image, the displacement amount corresponding to displacement caused on the road by application of a load of the vehicle. The storage unit stores information indicating a relation between the load and the displacement amount. The load calculator calculates the load based on the displacement amount and the information.

A load meter includes a detector, a storage unit, and a load calculator. The detector detects, by using a captured image obtained by capturing a road and a vehicle present on the road, a displacement amount in the captured image, the displacement amount corresponding to displacement caused on the road by application of a load of the vehicle. The storage unit stores information indicating a relation between the load and the displacement amount. The load calculator calculates the load based on the displacement amount and the information.