R. Tiwari, Vinay Gautam, Vikrant Sharma, A. Jain, N. K. Trivedi
{"title":"保护印度丰富的舞蹈遗产:印度舞蹈形式的分类和文化遗产保护的创新数字管理解决方案","authors":"R. Tiwari, Vinay Gautam, Vikrant Sharma, A. Jain, N. K. Trivedi","doi":"10.1109/SCSE59836.2023.10215044","DOIUrl":null,"url":null,"abstract":"Deep connections exist between dance and cultural heritage. Dance is frequently passed down through generations as an essential component of a culture’s identity and as a means of maintaining and honoring that culture’s distinctive traditions and customs. A culture’s history, beliefs, and values can be powerfully expressed via dance, which can also be used for communication and storytelling. For the purpose of protecting and promoting India’s cultural legacy, it is crucial to comprehend how Indian dance styles are categorized. This paper proposes a hybrid Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) deep learning approach for the accurate classification of Indian dance style categories. The proposed model combines the strengths of both CNN and RNN to leverage spatial and temporal information, respectively, resulting in enhanced performance and improved accuracy. Extensive experiments were conducted to evaluate the performance of the proposed approach. The results demonstrate that the hybrid CNN-RNN model achieved an impressive accuracy of 97.74%, outperforming traditional methods and single-model architectures.","PeriodicalId":429228,"journal":{"name":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Preserving India’s Rich Dance Heritage: A Classification of Indian Dance Forms and Innovative Digital Management Solutions for Cultural Heritage Conservation\",\"authors\":\"R. Tiwari, Vinay Gautam, Vikrant Sharma, A. Jain, N. K. Trivedi\",\"doi\":\"10.1109/SCSE59836.2023.10215044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep connections exist between dance and cultural heritage. Dance is frequently passed down through generations as an essential component of a culture’s identity and as a means of maintaining and honoring that culture’s distinctive traditions and customs. A culture’s history, beliefs, and values can be powerfully expressed via dance, which can also be used for communication and storytelling. For the purpose of protecting and promoting India’s cultural legacy, it is crucial to comprehend how Indian dance styles are categorized. This paper proposes a hybrid Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) deep learning approach for the accurate classification of Indian dance style categories. The proposed model combines the strengths of both CNN and RNN to leverage spatial and temporal information, respectively, resulting in enhanced performance and improved accuracy. Extensive experiments were conducted to evaluate the performance of the proposed approach. The results demonstrate that the hybrid CNN-RNN model achieved an impressive accuracy of 97.74%, outperforming traditional methods and single-model architectures.\",\"PeriodicalId\":429228,\"journal\":{\"name\":\"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SCSE59836.2023.10215044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Research Conference on Smart Computing and Systems Engineering (SCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCSE59836.2023.10215044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Preserving India’s Rich Dance Heritage: A Classification of Indian Dance Forms and Innovative Digital Management Solutions for Cultural Heritage Conservation
Deep connections exist between dance and cultural heritage. Dance is frequently passed down through generations as an essential component of a culture’s identity and as a means of maintaining and honoring that culture’s distinctive traditions and customs. A culture’s history, beliefs, and values can be powerfully expressed via dance, which can also be used for communication and storytelling. For the purpose of protecting and promoting India’s cultural legacy, it is crucial to comprehend how Indian dance styles are categorized. This paper proposes a hybrid Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) deep learning approach for the accurate classification of Indian dance style categories. The proposed model combines the strengths of both CNN and RNN to leverage spatial and temporal information, respectively, resulting in enhanced performance and improved accuracy. Extensive experiments were conducted to evaluate the performance of the proposed approach. The results demonstrate that the hybrid CNN-RNN model achieved an impressive accuracy of 97.74%, outperforming traditional methods and single-model architectures.