Research on Chinese traditional opera costume recognition based on improved YOLOv5

Abstract

In order to protect the cultural heritage of opera costumes, establish visual labels for opera costumes, accelerate the establishment of a database for opera costumes, and increase the dissemination of opera culture, we propose an improved You Only Look Once (YOLO) v5-based opera costume recognition model for opera costumes with a wide range of styles, rich colors, and complex stage environments. By adding Coordinate Attention (CA) mechanism to the backbone of YOLOv5, the network can focus on more interesting information when extracting features; replacing the original feature pyramid module with a weighted bidirectional feature pyramid module in the Neck part to achieve efficient fusion of features; replacing the original loss function GIOU with DIOU to improve the detection accuracy and convergence speed. The average detection accuracy of the improved YOLOv5 model reaches 86.3% and its inference speed reaches 28 ms per frame through experiments on the homemade Chinese costume dataset, which improves the average detection accuracy by 3.1% compared with the original model, and has good robustness in detecting complex scenes such as covered targets, light-colored costumes, cross targets, dense targets and different angles. The model meets the requirements for accuracy and real-time costume recognition in complex theatrical environments.

Research on Fabric Defect Detection Algorithm Based on Improved YOLOv8n Algorithm

“…Therefore, this study adopts this concept, utilizing the LSKNet a ention mechanism to innovatively design the c2f-LSKNet, which incorporates LSKNet into both ends of the C2F module, thereby broadening the context regions to enhance the model's feature extraction capabilities. Liu et al integrated the AFPN module into the YOLOv5 algorithm, significantly enhancing its detection accuracy, especially for passion fruits containing small defects, in their quality classification efforts [20]. In this study, the original PAN-FPN module in YOLOv8n is replaced by AFPN, adopting a progressive fusion approach that first fuses low-level features, then mid-level, and finally top-level features.…”

Big Data Analysis of TikTok in the Education of Traditional Chinese Opera

“…However, at present, the number of short video playback of traditional opera is still relatively high. The reasons for this are analyzed with the modern communication theory of use and satisfaction [5]. Taking the study of opera inheritance as an example, from the audience's perspective, this paper analyzes the key technologies of mainstream informatization such as satisfaction [6], digitalization [7], big data [8], new media, Internet [9], and Chinese opera culture, and demonstrates and designs the main contents and basic methods of short video communication of Chinese opera culture.…”

CHERRY SEGMENTATION AND IDENTIFICATION BASED ON DeepLabV3 IN COMPLEX ORCHARD ENVIRONMENT

“…Hence, utilizing deep learning to realize the segmentation and identification for cherry is a pivotal step in the industrialization process of cherry (Shuvo et al, 2021). In recent years, deep learning has been widely applied in computer vision task, focusing on solving the problems of segmentation , detection (Wang and He, 2021), recognition (Liu et al, 2023), and target tracking (Lu et al, 2021). Among them, image segmentation is the process of understanding images at pixel levels and obtaining target category labels corresponding to each pixel, which has received widespread attention in the field of agriculture.…”