Abstract: A display substrate includes: a base substrate, a plurality of pixel units and a plurality of initialization voltage signal lines. The pixel units are arranged in an array to form a plurality of rows of pixel units and a plurality of columns of pixel units, at least one pixel unit includes sub-pixels, and at least one sub-pixel includes a light-emitting element and a pixel driving circuit. The initialization voltage signal lines are configured to provide initialization voltage signals to the plurality of rows of pixel units respectively, and are arranged at intervals along a second direction. At least one initialization voltage signal line extends along a first direction. The plurality of rows of pixel units include a (2n?1)th row and a 2nth row and pixel driving circuits of the (2n?1)th row and pixel driving circuits of the 2nth rows share a common initialization voltage signal line.

Abstract: In an optical character recognition system, a word segmentation method, comprising: acquiring a sample image comprising a word spacing marker or a non-word spacing marker; processing the sample image with a convolutional neural network to obtain a first eigenvector corresponding to the sample image, a word spacing probability value and/or a non-word spacing probability value corresponding to the first eigenvector; acquiring a to-be-tested image, and processing the to-be-tested image with the convolutional neural network to obtain a second eigenvector corresponding to the to-be-tested image, a word spacing probability value or a non-word spacing probability value corresponding to the second eigenvector; and performing word segmentation on the to-be-tested image by using the just obtained word spacing probability value or the non-word spacing probability value.

Abstract: In an optical character recognition system, a word segmentation method, comprising: acquiring a sample image comprising a word spacing marker or a non-word spacing marker; processing the sample image with a convolutional neural network to obtain a first eigenvector corresponding to the sample image, a word spacing probability value and/or a non-word spacing probability value corresponding to the first eigenvector; acquiring a to-be-tested image, and processing the to-be-tested image with the convolutional neural network to obtain a second eigenvector corresponding to the to-be-tested image, a word spacing probability value or a non-word spacing probability value corresponding to the second eigenvector; and performing word segmentation on the to-be-tested image by using the just obtained word spacing probability value or the non-word spacing probability value.

Abstract: Various embodiments for detecting defects on a wafer are provided. Some embodiments include matching a template image, in which at least some pixels are associated with regions in the device having different characteristics, to output of an electron beam inspection system and applying defect detection parameters to pixels in the output based on the regions that the pixels in the output are located within to thereby detect defects on the wafer.

Abstract: A method of inspecting an array having memory blocks and page breaks. The array is imaged, and the image is divided into sections. Sections that include the memory blocks are selected into a candidate image. Pixels within a boundary horizontal line of pixels are inspected to determine horizontal edges of the memory blocks. Pixels within a boundary vertical line of pixels are inspected to determine vertical edges of the memory blocks. An image of a first memory block is compared to an image of a second memory block to determine differences. The differences are flagged as potential memory block defects. Images of the page breaks are compared to determine differences, and the differences are flagged as potential page break defects.

Abstract: Methods and systems for binning defects detected on a specimen are provided. One method includes comparing a test image to reference images. The test image includes an image of one or more patterned features formed on the specimen proximate to a defect detected on the specimen. The reference images include images of one or more patterned features associated with different regions of interest within a device being formed on the specimen. If the one or more patterned features of the test image match the one or more patterned features of one of the reference images, the method includes assigning the defect to a bin corresponding to the region of interest associated with the reference image.

Abstract: Methods and systems for binning defects detected on a specimen are provided. One method includes comparing a test image to reference images. The test image includes an image of one or more patterned features formed on the specimen proximate to a defect detected on the specimen. The reference images include images of one or more patterned features associated with different regions of interest within a device being formed on the specimen. If the one or more patterned features of the test image match the one or more patterned features of one of the reference images, the method includes assigning the defect to a bin corresponding to the region of interest associated with the reference image.

Abstract: A method of inspecting an array having memory blocks with page breaks disposed between them. The memory array is imaged with a sensor at a magnification such that the memory cell size is a whole integer pixel multiple within the sensor. This creates an array image that is divided into sections. Those sections that include at least a portion of the memory blocks are selected into a candidate image. Pixels of the image within a boundary distance of a horizontal single line of pixels are inspected to determine horizontal edges of the memory blocks to an accuracy of a single pixel. Pixels of the image within a boundary distance of a vertical single line of pixels are inspected to determine vertical edges of the memory blocks to an accuracy of a single pixel.

Abstract: A method of inspecting an array having memory blocks with page breaks disposed between them. The memory array is imaged with a sensor at a magnification such that the memory block size is a whole integer pixel multiple within the sensor. This creates an array image that is divided into sections. Those sections that include at least a portion of the memory blocks are selected into a candidate image. Pixels of the image within a boundary distance of a horizontal single line of pixels are inspected to determine horizontal edges of the memory blocks to an accuracy of a single pixel. Pixels of the image within a boundary distance of a vertical single line of pixels are inspected to determine vertical edges of the memory blocks to an accuracy of a single pixel.

Abstract: Methods and systems for binning defects detected on a specimen are provided. One method includes comparing a test image to reference images. The test image includes an image of one or more patterned features formed on the specimen proximate to a defect detected on the specimen. The reference images include images of one or more patterned features associated with different regions of interest within a device being formed on the specimen. If the one or more patterned features of the test image match the one or more patterned features of one of the reference images, the method includes assigning the defect to a bin corresponding to the region of interest associated with the reference image.