# Improved MSRN-Based Attention Block for Mask Alignment Mark Detection in Photolithography
## 1 Introduction  
Wafers chips are used in various industries as core components of electronic devices. The process for manufacturing a semiconductor consists of eight major processes and is divided into a front-end process for processing wafers and a back-end process for cutting and assembling chips in the processed wafer [1, 2]. Wafer fabrication, photo-etching, thin film deposition, metal wiring, oxidation and diffusion, ion implantation, chemical mechanical polishing, and cleaning processes are all included in the front-end. In addition, in the back-end, there are processes of electrical die sorting, packaging, and final inspection [3]. Various types of wafer defects occur whenever various processes are performed [4]. In particular, as the difficulty of implementing patterns increases with Pattern Shrink, great difficulties are experienced in overlay management [5]. A semiconductor is composed of a stacked structure of numerous layers, and a circuit is drawn according to an existing design pattern by sequentially stacking layers of conductors and insulators on the wafer through exposure and etching processes. The overlay vertically stacks the patterns formed on each layer in precise positions, and precise alignment technology is required to increase the overlay value [6]. Additionally, a Critical Dimension (CD) is used to describe the horizontal uniformity of the circuits. The minimum line width is the distance between the patterns, and the CD value should not vary depending on the position of the wafer. The CD value is uniform when measured at the wafer's center and edge [7]. Using the detected overlayed data, an overlay correction value is calculated and fed back to the exposure apparatus to prevent misalignment defects in subsequent wafers. Each unit process guarantees a high production yield and isdeveloped to strengthen competitiveness in the semiconductor manufacturing industry. Methods and devices for measuring process errors in each unit process are being actively researched. Through technology development, an optimization process is being formed in photolithography, and the performance of major equipment in the process is improving [8]. Misalignment of the photoresist pattern formed by exposure development is one of the considerations during photolithography. As semiconductor technology is highly integrated, alignment is becoming increasingly difficult due to problems such as reduction of alignment margin, transmittance due to level stacking structure, and an increase in wafer diameter and photolithography. Furthermore, misalignment problems occur due to problems such as wafer stage defects, reticle stage defects, and lens defects. To prevent misalignment defects, it is essential to optimize the overlay measurement process, which is an operation to check the alignment of the photoresist pattern formed on the wafer. A machine vision system is a special optical device that acquires an image from a digital sensor protected inside an industrial camera, through which computer hardware and software process and measure various characteristics for decision making [9; 10]. Image processing technology has recently advanced, and camera devices and sensors in production and manufacturing environments have become more intelligent. Additionally, manufacturing process optimization and autonomous correction of manufacturing conditions are becoming possible. Image and image processing technology that achieves high resolution and precision is increasing, and the introduction of visual sensors using images, lasers, lidars, and ultrasonic waves is expanding [11]. When a camera creates an image, the resolution of vision is a numerical expression of a scale that can express an object in detail, and the higher the number of pixels in the photosensitive area, the higher the resolution. To increase the accuracy of object recognition using machine vision, it is necessary to improve the resolution [12].