Abstract: A semiconductor structure includes a first interposer; a second interposer laterally adjacent to the first interposer, where the second interposer is spaced apart from the first interposer; and a first die attached to a first side of the first interposer and attached to a first side of the second interposer, where the first side of the first interposer and the first side of the second interposer face the first die.

Abstract: An image analysis device may align an image to determine a position of a wafer within the image. The wafer may include a plurality of wafer bumps. The image analysis device may mask, based on the position of the wafer, the image to obtain an image of a portion of the wafer. The image analysis device may binarize the image of the portion of the wafer to create a binarized image of the portion of the wafer. The image analysis device may determine a bump pattern, associated with the plurality of wafer bumps, based on the binarized image of the portion of the wafer. The image analysis device may perform a defect analysis of the determined bump pattern. The defect analysis may be associated with detecting regions of the portion of the wafer in which one or more wafer bumps have abnormal bump heights.

Abstract: A method for detecting a three-dimensional object in a two-dimensional image includes: inputting the two-dimensional image into an object detection model, and obtaining a resulting detection depth dataset; obtaining, based on the detection depth dataset, coordinate sets of a number of points-of-interest each associated with a to-be-detected object in a 3D camera centered coordinate system; and converting the coordinate sets of the number of points-of-interest in the 3D camera centered coordinate system into a number of coordinate sets in a 3D global coordinate system. Embodiments of this disclosure may be utilized in the field of self-driving cars with roadside traffic cameras.

Abstract: A method for performing automatic license plate recognition includes: performing character detection on a to-be-processed image; when a number of character objects constituting characters of a license plate are detected, obtaining a representative point for each character object; calculating a pattern line with respect to the character objects; calculating a skew angle defined by the pattern line and a preset reference line; rotating each character object based on the skew angle to obtain an adjusted image; and performing character recognition on the adjusted image to obtain a recognized character for each character object.

Abstract: A method for performing automatic license plate recognition includes: performing character detection on a to-be-processed image; when a number of character objects constituting characters of a license plate are detected, obtaining a representative point for each character object; calculating a pattern line with respect to the character objects; calculating a skew angle defined by the pattern line and a preset reference line; rotating each character object based on the skew angle to obtain an adjusted image; and performing character recognition on the adjusted image to obtain a recognized character for each character object.