With the prevalence of tissue stains and fluorophores used as visualization tools in the life sciences and specifically in microscopy, consideration of the viewer’s ability to discriminate color variation becomes relevant. This abstract is presented so that those within the microscopy community might be aware of the prevalence of color vision deficiency and to suggest easily accessed tools whic...

All RDs are accompanied by some loss of visual function but this will vary depending upon the type of detachment, its size, and retinal location, making it difficult to ascribe one set of symptoms to the condition (Box 71.3). Diagnosing RD is complex with many qualifications. Abnormal vision is the only reliable symptom of RD. But the types of abnormal vision are large and varied: light flashes...

Tube yarn is also called glass fiber spun yarn. Due to the excellent properties of fiber, various industrial products based on are used in a variety industries. As most obvious factor affecting quality products, detection yarns very important for companies. traditional defect relies experience and subjective factors workers, which makes many different views same defect. Some methods limit solut...

Abstract With the development of semiconductor assembly technology, continuous requirement for improvement chip quality caused an increasing pressure on manufacturing process. The defects pin had been mostly verified by manual inspection, which has low efficiency, high cost, and reliability. In this paper, we propose a vision measurement method to detect defects, such as warping collapse that h...

Steel plays an important role in industry, and the surface defect detection for steel products based on machine vision has been widely used during last two decades. This paper attempts to review state-of-art of vision-based inspection technology by investigating about 170 publications. covers overall aspects including hardware system, automated method, existing problems latest development. The ...

A crucial part of image classification consists capturing non-local spatial semantics content. This paper describes the multi-scale hybrid vision transformer (MSHViT), an extension classical convolutional neural network (CNN) backbone, for multi-label sewer defect classification. To better model in images, features are aggregated at different scales non-locally through use a lightweight transfo...