A system can receive downhole acquisition data relating to a wellbore. The system can pre-process the downhole acquisition data. The system can generate an incomplete borehole image using the downhole acquisition data. The system can determine a sparse representation based on the incomplete borehole image by performing an optimization with respect to the incomplete borehole image. The system can generate a complete borehole image based on an inverse of the sparse representation.

A process includes receiving a target quality value, receiving a measured quality value, receiving a source quality value, and sending a source control instruction. The source control instruction is based at least in part on the target quality value, the measured quality value, and the source quality value. The target quality value, the measured quality value, the source quality value, and the source control instruction are communicated via the communication port. The measured quality value is generated by an inspection device configured to inspect a sample. The source quality value is associated with a quality level of a first group of samples. The target quality value indicates a desired quality value of an output group of samples. The source control instruction causes a source selecting device to select one of a plurality of groups of samples, each group having identified quality characteristics.

A vision inspection system includes a sorting platform having an upper surface supporting parts for inspection, wherein the parts are configured to be loaded onto the upper surface of the sorting platform in a random orientation. The vision inspection system includes an inspection station including an imaging device. The vision inspection system includes a vision inspection controller receiving images and processing the images based on an image analysis model to determine inspection results for each of the parts. The vision inspection controller has a shape recognition tool configured to recognize the parts in the field of view regardless of the orientation of the parts on the sorting platform. The vision inspection controller has an AI learning module operated to customize and configure the image analysis model based on the images received from the imaging device.

Systems and methods for generating assessments based on construction site images are provided. For example, image data captured from a construction site using at least one image sensor may be obtained. Further, at least one electronic record associated with the construction site may be obtained. The image data and the at least one electronic record may be analyzed to generate at least one assessment related to the construction site. For example, the image data may be analyzed to identify at least one discrepancy between the at least one electronic record and the construction site, and the identified at least one discrepancy may be used in the generation of the at least one assessment.

Automated vehicle repair estimation by aggregate ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a plurality of vehicle repair recommendation sets for a damaged vehicle, wherein each of the vehicle repair recommendation sets identifies at least one recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; aggregating a plurality of the recommended vehicle repair operations; generating a composite vehicle repair recommendation set that identifies the aggregated recommended vehicle repair operations; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.

A method of inspecting a structure during additive manufacturing of the structure and additive manufacturing systems are presented. An additive manufacturing system comprises additive manufacturing equipment comprising a casing and an additive manufacturing head configured to form a plurality of layers of a structure within the casing; and an x-ray backscatter imaging system configured to send an x-ray beam into a structure formed within the additive manufacturing equipment and detect scattered x-rays for imaging and analysis of the structure during fabrication.

A gardening apparatus includes one or more of a base, a fluid reservoir, and a plant tray or support disposed on the reservoir. The support is adapted for receiving one or more modular plant inserts, and can define a flow structure for channeling fluid to each insert. A pump supplies fluid from the reservoir to the plant tray or support, with a light assembly adapted to generate a spectrum of light for growth of plants from the inserts. A processor is configured for controlling fluid flow from the pump, the light spectrum generated by the lighting elements, or both. For example, the processor can use a dynamic recipe, algorithm or control schedule to modulate the fluid flow or spectrum based the plant type, growth stage, height, plant health data, digital phenotyping data, or ambient conditions, or a combination thereof.

An improved method for examining an article by using a vision system is presented. Also presented is a vision system for use within such a method.

A method for producing and classifying polycrystalline silicon. The method includes producing polycrystalline silicon rod within a reaction space of a gas phase deposition reactor by introducing a reaction gas, which in addition to hydrogen contains silane and/or at least one halosilane. Once produced, the polycrystalline silicon rod is extracted from the reactor, and at least one two-dimensional and/or three-dimensional image is generated of at least one partial region of the polycrystalline silicon rod or of at least one silicon chunk created. At least one analysis region is selected per generated image and at least two surface-structure indices per analysis region are generated by using image processing methods, each of which is generated using a different image processing method. The surface-structure indices are combined to form a morphology index.

A method of identifying a defect in a wet film comprises conveying said wet film (20), in a wet state, on a conveyor (10), providing a laser projection (1511) onto the wet film, acquiring a series of images, each depicting an area of the wet film, wherein at least a portion of the laser projection is visible, and using at least some of said images to identify said defect. There is also disclosed a method and device for producing a film.