Content-Based Video Retrieval Using Integration of Curvelet Transform and Simple Linear Iterative Clustering

Mounika, B.; Khare, Ashish; Khare, Manish; Palanisamy, P.

doi:10.1142/s0219467822500188

Cited by 5 publications

(3 citation statements)

References 37 publications

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“…Content-based audio information retrieval should be simple and accurate. The so-called simplicity refers to the user's ability to use the retrieval system simply and conveniently, without the need to master the relevant domain expertise [30][31]. Accuracy means that the search results should be as close as possible to the user's search requirements.…”

Section: Multimedia Retrievalmentioning

confidence: 99%

Construction of law and economics litigation service platform based on multimedia retrieval

Cai

2023

Applied Mathematics and Nonlinear Sciences

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Legal economics uses empirical research to analyze and predict the effects of various legal system arrangements to better explain whether the actual effect of the law is consistent with the expected effect of the law. Artificial Intelligence (AI) has become the core driving force of the new round of scientific and technological revolutions, and the trend of cross-border integration is becoming more and more obvious. Therefore, the intelligent construction of a legal litigation platform is the only way for social development. Litigation service management is a platform that uses big data technology to process and facilitate the information development of legal litigation services. In the face of the rapid changes in legal litigation services, an intelligent litigation service management platform is needed to serve the public. Given the above defects, this paper proposes a law and economics litigation service management platform based on multimedia retrieval, including a litigation service management system, a queuing system, and an autonomous operating system. The litigation service management system is connected with the queuing system and autonomous operating system, respectively. We provide a litigation service management platform to provide efficient operations with humanized functions to assist and improve the service quality of legal litigation services. At the same time, we combined the current application status of AI in grassroots courts and the actual work to analyze the difficulties and problems faced, draw lessons from the successful experience of some courts in China, and find out the direction and path for the application and promotion of AI in grassroots courts.

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Section: Multimedia Retrievalmentioning

confidence: 99%

Construction of law and economics litigation service platform based on multimedia retrieval

Cai

2023

Applied Mathematics and Nonlinear Sciences

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“…e traditional method is to annotate and classify these videos manually, thus, forming a database of dance videos that can be indexed by keywords. However, with the huge amount of dance video data, it would take a lot of human resources, money, and time to use the manual annotation method [11][12][13]. is manual approach requires staff to face a large amount of dance video data every day, which is prone to visual errors, thus, leading to errors in video annotation and classification.…”

Section: Introductionmentioning

confidence: 99%

Dance Art Scene Classification Based on Convolutional Neural Networks

2022

Scientific Programming

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Digital multimedia resources have become an important part of people’s daily cultural life. Automatic scene classification of a large number of dance art videos is the basis for scene semantic based video content retrieval. In order to improve the accuracy of scene classification, the videos are identified using a deep convolutional neural network based on differential evolution for dance art videos. First, the Canny operator is used in YCbCr colour space to detect the human silhouette in the key frames of the video. Then, the AdaBoost algorithm based on cascade structure is used to implement human target tracking and labelling, and the construction and updating of weak classifiers are analysed. Next, a differential evolution algorithm is used to optimise the structural parameters of the convolutional neural network, and an adaptive strategy is adopted for the scaling factor of the differential evolution algorithm to improve the optimisation solution accuracy. Finally, the improved deep convolutional neural network is used to train the classification of the labelled videos in order to obtain stable scene classification results. The experimental results show that by reasonably setting the crossover rate of differential evolution and the convolutional kernel size of the convolutional neural network, high scene classification performance can be obtained. The high accuracy and low root-mean-square error validate the applicability of the proposed method in dance art scene classification.

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“…Data mining is the process of extracting potentially useful information and knowledge from fuzzy, random realworld application data [11][12][13][14]. e data source must be real and noise-laden.…”

Section: Introductionmentioning

confidence: 99%

Tunnel Security Management Based on Association Rule Mining under Hadoop Platform

Wang

Xue²

2022

Mathematical Problems in Engineering

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The problem of how to use large amounts of historical data for tunnel safety management has a greater practical application value. The association rule method in data mining technology can provide effective decision support for tunnel safety prevention by mining historical data. To address the problem of large data volume and sparse data items in tunnel safety management, an association rule method—Apriori algorithm—based on the Hadoop platform is proposed to improve the efficiency and accuracy of data mining in cloud environment. First, the parallel MapReduce implementation steps are analyzed on the basis of the distributed Hadoop framework. Then, the existing single-user data validation algorithm is improved by applying a multiuser parallel validation algorithm to Apriori in order to reduce the number of validations. Next, the traditional association rule Apriori algorithm is MapReduce optimized to generate a smaller set of useless candidate items. At the same time, Boolean ranking is used to optimize the way transactional data are stored in the database, reducing the number of redundant subsets and the number of times the database is connected, and shortening the task processing time. The experimental results show that the proposed method is able to mine the relationships between tunnel safety hazards and provide effective decision support for tunnel safety prevention. At the same time, the proposed method more efficiently operates than other association rule methods.

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Content-Based Video Retrieval Using Integration of Curvelet Transform and Simple Linear Iterative Clustering

Cited by 5 publications

References 37 publications

Construction of law and economics litigation service platform based on multimedia retrieval

Construction of law and economics litigation service platform based on multimedia retrieval

Dance Art Scene Classification Based on Convolutional Neural Networks

Tunnel Security Management Based on Association Rule Mining under Hadoop Platform

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