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Research on Hybrid Path Planning Algorithm Based on Anti-Collision

Research on Hybrid Path Planning Algorithm Based on Anti-Col...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Penghao Ren Mengnan Li Zhibin Su Beijing Radio & Television Station Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Communication University of China Beijing Key Laboratory of Modern Entertainment Technology Communication University of China Beijing China

In order to solve the problem of fast switching of special equipment in the cultural complex, the improved Moth-Flame Optimization algorithm (MFO) is combined with the improved Dynamic Window Approach (DWA) to realize the hybrid path planning of handling robots in different scenarios of cultural complexes in this paper. Specifically, the traditional Moth-Flame Optimization algorithm is improved and applied to the global path planning problem. On the basis of the planned global path, the intersection of dynamic obstacles with the global path is detected, and the improved Dynamic Window Approach is used for local obstacle avoidance in the section with collision risk, finally, the hybrid path planning in the complex environment of the cultural complex is realized. The simulation experimental results prove the effectiveness of the proposed algorithm.

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Source Separation of Piano Concertos Using Hybrid LSTM-Transformer Model

Source Separation of Piano Concertos Using Hybrid LSTM-Trans...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： JingYu Liu Wei He Jingjing Zhou Wei Jiang State Key Laboratory of Media Convergence and Communication Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China School of Information and Communication Engineering (Communication University of China) Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Music source separation, the process of extracting independent audio streams from a complex mix, has traditionally focused on isolating vocals, drums, bass, and other primary sources. This study tackles the more intricate task of separating the piano component from a piano concerto-a challenge compounded by the diverse range of instruments and the dynamic shifts in volume and timbre. Unlike traditional music separation tasks, the piano’s distinct characteristics and its interaction with the orchestra demand a more nuanced *** address the scarcity of multi-track recordings for piano concertos, this research pioneers an artificial data synthesis strategy to create a robust training dataset. We introduce a novel hybrid deep learning model that integrates Long Short-Term Memory (LSTM) networks with Transformer architecture, capitalizing on their complementary strengths to distinguish piano melodies from the rich tapestry of orchestral sounds. Our experiments demonstrate that this hybrid approach significantly outperforms conventional methods, with an improvement of 3.18 dB in signal-to-distortion ratio. These results not only validate the efficacy of proposed method but also pave the way for innovative applications in classical music source separation.

关键词： Training Deep learning Source separation Instruments Transformers Recording Timbre

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Classification of Dunhuang Mural Image Based on Small-sample and Semi-supervised Learning

Classification of Dunhuang Mural Image Based on Small-sample...

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IEEE Information technology, Networking, Electronic and Automation control Conference

作者： Hui Cui Zhibin Su Luyue Zhang Liyang Bai School of Information and Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Center for Ethnic and Folk Literature and Art Development Ministry of Culture and Tourism P.R.C.

Dunhuang mural images classification belongs to the research task in the field of image recognition. In this paper, the semi-supervised model is established with multidimensional features extracted by transfer learning. A small number of labeled samples were used to obtain a large number of unlabeled data, combined with Active Learning and iterative strategy for multiple rounds of label transfer of selected samples. After several rounds of iterations, we can get a more powerful classification learner. Experiments on the self-built Dunhuang mural dataset have shown that the results can approach or even exceed some supervised learning methods when the number of known label samples is less than 4%. Our research implements the cultural resource image classification algorithm based on small samples, which is conductive to improving the accuracy when label samples are scarce.

关键词： Technological innovation Transfer learning Supervised learning Semisupervised learning Predictive models Feature extraction Classification algorithms

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Study on the classification of beatbox sounds based on timbre features

Study on the classification of beatbox sounds based on timbr...

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Culture-oriented Science & technology (ICCST), International Conference on

作者： Jiaxing Zhu Junping Wang Jingyu Liu Xiaoyi Zhang Conservatory of Music Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology Communication University of China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Beatbox is a performance form of vocal percussion, which is gradually favored by people with continuous development in recent years. With the abundance of Beatbox content on the Internet, the research on its automatic classification becomes very significant. In this article, we mainly using machine learning methods, to identify the beatbox timbre. First of all, we collected 900 Beatbox audio materials and constructed a database. Secondly, 14 acoustic parameters of audio material are extracted by the signal processing method. Finally, we used MultilayerPerceptron, SMO, BayesNet, RandomForest in current machine learning to build a training model for BB timbre classification. The Experimental results showed that the model could classify BB timbre well.

关键词： Timbre Classification algorithms Machine learning algorithms acoustics Music Training Signal processing algorithms

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Design and Implementation of an Linkage control system for Stage visual Effect Equipment

Design and Implementation of an Linkage Control System for S...

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Culture-oriented Science & technology (ICCST), International Conference on

作者： Shilei Bai Yihan Suo Kai Xu Xiujun Tang Jiaxin Zhang School of Information and Communication Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism (Communication University of China) Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) State Key Laboratory of Media Convergence of Communication Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

In view of the problems of low equipment integration, difficult equipment operation, and high technical threshold existing in the current stage visual effect linkage control system, a highly integrated linkage control system for stage visual effect equipment, which is suitable for small and medium-sized performance venues, is proposed in this paper. This system can control the stage lighting and the playback of multi-channel and multi-format media content, and it is easy to control. The design scheme of the system is described in detail, and the feasibility of the system is verified through tests in this paper.

关键词： visual effects Lighting Couplings control systems Libraries Software Process control

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Joint Depth Estimation and Semantic Segmentation with Adversarial Multi-task Network

Joint Depth Estimation and Semantic Segmentation with Advers...

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Culture-oriented Science & technology (ICCST), International Conference on

作者： Hui Ren Nan Gao Jia Li State Key Laboratory of Media Convergence of Communication Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China Beijing China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Some exiting works have explored the promotion between depth estimation and semantic segmentation. These works are usually based on convolutional neural networks, which extract compact features and map the relationship between input and output according to specific tasks. In this paper, we introduce a novel adversarial training strategy, that is, generator produces the semantic segmentation map and depth map, and then the discriminator can judge the authenticity of the synthesized color image, thereby supervising the output of the network during back propagation. We use the adversarial loss combined with the reconstruction loss function to supervise the model, and find that the adversarial loss function which is seen as a global supervision can further optimize the output. We use 200 color images from Kitti dataset with semantic segmentation ground truth as the training set, and train the network in an end-to-end manner. The experimental results show that the adversarial training method is well applied to the multi-task training combining semantic segmentation and depth estimation, and can further improve the quantitative performance of depth estimation.

关键词： Semantics Estimation Generative adversarial networks Generators Training Task analysis Mathematical model

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Association Between Timbre Perception Features and Fine-Grained Emotions in Film and Television Music

Association Between Timbre Perception Features and Fine-Grai...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Xiaomeng Ren Zhibin Su Wei Jiang Jingyu Liu State Key Laboratory of Media Convergence and Communication (Communication University of China) China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism (Communication University of China) China School of Information and Communication Engineering (Communication University of China) China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

As an integral component of modern cultural works, the role of film and television music in artistic expression and emotional communication has become increasingly significant. Timbre, as a crucial attribute of music, has primarily been studied in terms of the influence of its fundamental objective parameters on coarse-grained emotions. However, there is a lack of in-depth exploration of the association between timbre perception features and fine-grained emotion. Consequently, this paper approaches from the perspective of timbre perception features and fine-grained emotions in film and television music. By conducting perceptual evaluation and subjective emotional annotation experiments, it analyzes the correlation between timbre perception features and fine-grained emotions, confirming that timbre perception features significantly influence musical emotions. Furthermore, a multivariate linear regression model was employed to construct a fine-grained emotion prediction model, which has demonstrated good predictive ability for most musical emotions. This research provides a new perspective on understanding the relationship between timbre and emotion in film and television music, offering a scientific basis for its creation and performance.

关键词： TV Costs Correlation Annotations Linear regression Predictive models Timbre

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Multipath planning based on multimodal optimization slime mold algorithm

Multipath planning based on multimodal optimization slime mo...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Luli Gao Hui Ren School of Information and Communication Engineering Communication University of China Bejing China Key laboratory of Acoustic Visual Technology and Intelligent Control System(Communication University of China)Ministry of Culture and Tourism Bejing China Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) Bejing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Multipath planning aims to find multiple optimal paths simultaneously, and its essence is a multimodal optimization problem. In recent years, swarm intelligence (SI) optimization algorithms have provided effective solutions for multimodal optimization. In this paper, the multimodal optimization slime mold algorithm (MOSMA) based on master-slave structure and local search strategy (LS) is proposed to solve multipath planning problems in small cultural complex. Firstly, a local search strategy is introduced to eliminate the influence of the “centerbias” operator and improve the quality of solutions. Secondly, the master-salves structure is introduced to preserve the diversity of the population and enable it to simultaneously locate multiple solutions. Finally, the performance of MOSMA is analyzed on several multimodal functions, and an example of path planning in a small cultural complex is given.

关键词： Location awareness Costs Search problems Main-secondary Path planning Planning Cultural differences

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A Study on the Relationship Between Timbre Perception Features and Emotion in Musical Sounds

A Study on the Relationship Between Timbre Perception Featur...

引用

Culture-oriented Science & technology (ICCST), International Conference on

作者： Jiying Guo Jingyu Liu Zijin Li Jiaxing Zhu Wei Jiang State Key Laboratory of Media Convergence of Communication Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) School of Information and Communication Engineering Communication University of China China Conservatory of Music Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

This paper mainly studies the relationship between timbre perception features and emotion in musical sounds. Firstly, a five - dimensional emotional space was determined by multidimensional scaling analysis. Then emotional labeling subjective evaluation experiments were carried out for 72 scale materials and 48 melody materials of timbre to obtain emotional data of timbre materials. The correlation between timbre perception features and emotion is studied according to the playing content, temporal characteristics, and musical instrument types. Finally, a set of mathematical models of the relationship between timbre perception features and emotion was established by the method of multiple linear regression. The experimental results show that the features of timbre perception are an important effect on musical emotion, and these models have good predictive ability for the five emotion dimensions.

关键词： Timbre Instruments Correlation Correlation coefficient Standards Aerospace electronics Semantics

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Research on Mural Restoration Method Based on Generative Multi-column Transformer

Research on Mural Restoration Method Based on Generative Mul...

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IEEE Advanced Information Management,Communicates,Electronic and Automation control Conference (IMCEC)

作者： Hui Ren Fanhua Zhao Zhen Li Ke Sun Shilin Gao State Key Laboratory of Media Convergence and Communication Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) Center for Ethnic and Folk Literature and Art Development Ministry of Culture and Tourism Beijing China

ISBN: (纸本)9781665479691

Ancient mural are splendid artistic treasures of ancient civilizations, but their blurring and destruction are becoming more and more serious due to the effects of time and environment. In this paper, a Generative Multi-column Transformer method is proposed to recover the missing areas of mural. The method synthesizes different image components in a parallel manner by transformer and enhances local details by employing implicit diversified Markov random fields regularization. Generative Multi-column Transformer is used in combination with reconstruction and Markov random field loss methods to propagate local and global information from the background to the target defaced region to reconstruct the loss in that part. The experimental results show that the method based on Generative Multi-column Transformer adopted in this paper is able to restore mural images with complex textures and missing areas very well, while the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) of the method are improved, this paper provides theoretical guidance for the digital restoration of murals.

关键词： Measurement visualization PSNR Transformers Propagation losses Feature extraction Image restoration

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