A method (400) of capturing and processing electroluminescence (EL) images (1910) of a PV array (40) is disclosed herein. In a described embodiment, the method 400 includes controlling the aerial vehicle (20) to fly along a flight path to capture EL images (1910) of corresponding PV array subsections (512b) of the PV array (40), deriving respective image quality parameters from at least some of the captured EL images, dynamically adjusting a flight speed of the aerial vehicle along the flight path, based on the respective image quality parameters for capturing the EL images (1910) of the PV array subsections (512b), extracting a plurality of frames (1500) of the PV array subsection (512b) from the EL images (1910); determining a reference frame having a highest image quality of the PV array subsection (512b) from among the extracted frames (2100); performing image alignment of the extracted frames (2100) to the reference frame to generate image aligned frames (2130), and processing the image aligned frames (2130) to produce an enhanced image (2140) of the PV array subsection (512b) having a higher resolution than the reference frame. A system, image processing device, and aerial vehicle for the method thereof are also disclosed.

An image inspection device includes: an image acquisition unit to acquire an inspection target image; a geometric transformation processing unit to estimate a geometric transformation parameter for aligning a position of an inspection target in the inspection target image with a first reference image in which a position of the inspection target is known, and geometrically transform the inspection target image using the estimated geometric transformation parameter, thereby generating an aligned image in which the position of the inspection target is aligned with the first reference image; an image restoration processing unit to restore the aligned image, using an image generation network to receive an input image generated using the inspection target image and infer the aligned image as a correct image; and an abnormality determination unit to determine an abnormality of the inspection target using a difference image between the aligned image and the restored aligned image.

A method, system, and computer-readable medium, for detecting whether an eye blink or non-blink is captured in the image. The method includes filtering, from the image, one or more objects that are predicted to be unsuitable for determining whether an eye blink or no-blink is captured in the image, to provide a filtered image. The method also includes correlating the filtered image with a reference image, and determining, based on the correlating, whether the eye blink or non-blink is captured in the image. The eye blink is a full eye blink or a partial eye blink, and the images may be sequentially captured IR SLO images, in one example embodiment herein. Images determined to include an eye blink can be omitted from inclusion in a final (e.g., OCT) image.

Circuit board inspection by receiving a near infrared (NIR) image of at least a portion of a circuit board, analyzing the NIR image using a machine learning model, and detecting anomalous circuit board portions according to the analysis.

Various methods and systems are provided for tracking a biopsy target across one or more images. In one example, a method includes determining a position of a biopsy target in a selected image of a patient based on an image registration process with a reference image of the patient, and displaying a graphical representation of the position of the biopsy target on the selected image.

A method allows an estimator or other party to “Walk the Drawings.” An estimator can open one or more sets of drawings on a mobile device and walk those same electronic drawings as they actually walk or traverse the physical site itself. In other words, as the estimator physically moves across the construction site in the real world, their electronic icon (avatar) moves across the corresponding electronic drawings on their mobile device. Now the estimator can identify present and future such as features that need to be accessible being buried under asphalt. While walking the drawings, the estimator can label any challenges or features by simply clicking their avatar and it will post that geo-stamped location complete with corresponding notes and photos straight to the drawings for later review and analysis.

The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize a continuous kernel neural network that learns continuous reconstruction kernels to merge digital image samples in local neighborhoods and generate enhanced digital images from a plurality of burst digital images. For example, the disclosed systems can utilize an alignment model to align image samples from burst digital images to a common coordinate system (e.g., without resampling). In some embodiments, the disclosed systems generate localized latent vector representations of kernel neighborhoods and determines continuous displacement vectors between the image samples and output pixels of the enhanced digital image. The disclosed systems can utilize the continuous kernel network together with the latent vector representations and continuous displacement vectors to generated learned kernel weights for combining the image samples and generating an enhanced digital image.

A method for identifying a base in nucleic acid, a computer-readable storage medium, a computer program product, and a system. The method for identifying a base in nucleic acid comprises: mapping a coordinate of each bright spot in a bright spot set corresponding to a template onto an image to be inspected, and determining the position of a corresponding coordinate on said image (S11); determining the intensity of a signal at the position of the corresponding coordinate on said image, the intensity being a corrected intensity (S21); and comparing the intensity of the signal at the position of the corresponding coordinate on said image with the size of a first preset value, and determining a base type corresponding to the position on the basis of the comparison result, so as to achieve base calling (S31). The method may quickly and accurately identify a base, and achieve the determination of an order of nucleotides/bases of at least part of a sequence of a template.

The present disclosure generally pertains to systems and methods for detecting surface conditions using multiple images of different polarizations. A system in accordance with the present disclosure captures images having different polarizations and compares the images to evaluate surface conditions of an area, such as a runway, landing pad, roadway, or taxiway on which a vehicle is expected to land or otherwise travel. In some cases, a surface hazard, such as water, ice, or snow covering a surface of the area, may be detected and identified. Information indicative of the surface conditions may be used to make control decisions for operation of the vehicle.

An image processing apparatus includes at least one processor, and the processor derives three-dimensional coordinate information that defines a position of a structure in a tomographic plane from a tomographic image including the structure, and that defines a position of an end part of the structure outside the tomographic plane in a direction intersecting the tomographic image.