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The Miao nationality is the sixth largest ethnic group in China which has a history of thousands of years. It has created a unique material culture and spiritual culture in its development process and the Miao costume is a highly condensed collection of the material and spiritual culture of the Miao nationality. As one of the unique symbols of Miao culture the Miao costume has profound cultural heritage and cultural connotations. The patterns of the Miao costume are particularly eye-catching as they not only symbolize the wisdom of the Miao people in thousands of years of production and life but also symbolize the pursuit of the good spirit of the Miao people. However under the impact of modern pop culture and foreign culture these cultural symbols are gradually disappearing. In order to protect and inherit them the Miao costume pattern segmentation has become the most important work. However the Miao costume pattern segmentation is quite difficult. At present there are few studies on the extraction classification identification and preservation of the features of Miao costume pattern segmentation. With the excellent segmentation performance of the U-Net model and the advantages of easy deployment the paper improves the basic structure of the U-Net model and proposes a Miao costume pattern segmentation algorithm based on the RSKP-UNet Residual Selective-Kernel Parallel U-Net model. The algorithm adds Residual modules in the encoder part of the U-Net model to improve the feature extraction capability of the model and embeds the SKNet modules and ParNet modules in the decoder part to enhance the feature expression capability of the model. The paper uses evaluation metrics to measure the segmentation performance of the model and compares it with four segmentation models based on deep learning. The paper not only combines the current research focus-deep learning and attention mechanism but also introduces the Lovász-hinge loss function to effectively solve the problem of class imbalance in the Miao costume patterns. The RSKP-UNet model is better than other models in various segmentation indicators. Compared with the benchmark model U-Net the Dice coefficient IoU precision recall and accuracy are improved by 6. 98% 11. 07% 2. 89% 6. 75% and 3. 92% . The segmentation algorithm proposed in this paper realizes the extraction of the element content of the Miao costume patterns through image segmentation of Miao costume patterns which can be used to build the Miao costume pattern database in this way thus helping designers relevant researchers and organizations to provide research foundation and completing the protection and inheritance of the Miao costume culture. The paper also provides some reference for the segmentation research of other minority costume patterns. © 2022 Authors. All rights reserved. 相似文献
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城市经济的发展带动城市边缘区的建设与开发。文章通过对区位要素与空间区位特征的研究与分析,得出区位对每个区域的发展模式存有影响。各村屯要根据自己所处的地理位置特征,合理定位,制定相适应的、可行的、动态的发展模式。 相似文献
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江南民居的现代诠释与农居设计思考 总被引:2,自引:0,他引:2
该文从选址布局、院落空间、结构体系、建筑风格等方面概括和诠释了江南民居的特征和文化背景,通过东南沿海地区经济社会发展的分析,对现代村镇民居进行剖析和比较,从居住建筑因地制宜、舒适实用、灵活机动和地域特色的角度,阐述了东南沿海地区现代村镇建筑如何传承江南民居优点,适应现代生活的新理念. 相似文献
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传统村落旅游开发与形态变化研究 总被引:13,自引:1,他引:13
近十余年来,传统村落旅游持续升温,建筑学、地理学、旅游学等学科对这一现象进行了充分的研究,但对村落旅游开发与村落形态变化的研究却相对匮乏,在开展传统村落旅游研究中需弥补这一空白.根据旅游开发过程中村落形态的变化,把直接参与旅游的村落划分为渐变型、稳定型、突变型和恢复型4类.针对4种类型的村落,各选其一,从村落区域、边界、节点、标志物、民居、整体风貌等构成要素出发,探讨各类型村落的形态变化特征,构建村落形态变化的影响因素模型,指出村落的形态变化受到市县级政策与管理措施、开发商与规划师、村民收入与村落人口、传统建筑材料与建筑技术8种因素的影响. 相似文献
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宁波市鄞州区村庄布局规划探讨 总被引:3,自引:2,他引:3
村庄规划是涉及广大农民切身利益的一项全局性的重要工作,对促进社会主义新农村建设意义重大.在城乡空间布局规划的指导下,鄞州区村庄布局规划坚持以人为本、与区域发展相协调、集约利用土地等原则,将全区村庄划分为城市型、扩展型、保留型、撤并型和特色型五种类型进行规划,以引导村庄居民点由分散向集约发展. 相似文献
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通过龙胜温泉度假村的规划总结,解读在旅游区的规划设计中自然形态与设计形态如何互相和谐。 相似文献