Self-designed hierarchical network based hand shape intelligent recognition and evaluation for Chinese zither performing

A proper hand shape is the foundation for professional musical instrument performance. In this paper, the image recognition technology based on artificial intelligence is introduced into the hand shape recognition of performing Chinese zither, which is referred to as Zheng in Chinese, for the first time to realize the function of hand shape intelligent evaluation and the self-designed hierarchical network is proposed to recognize and evaluate correct hand shape for Zheng performing. The intra-class difference is larger than the inter-class difference for Zheng performing hand shape image, which belongs to fine-grained image. Therefore, we use the first layer network to determine four classes of images acquired from different viewpoints. Meanwhile, the feature maps from different convolutional blocks of this layer are concatenated as the input of the second layer, which performs fine classification of Zheng performing hand shape images. Consequently, the learning ability of the network can be improved and the complexity of the network can be reduced at the same time. We design an experimental paradigm for instrumentalist hand shape performance evaluation, formulate a Zheng hand shape evaluation merit based on image recognition, and construct a Chinese zither hand shape Dataset (CZ-dataset V3) for the real scene. The experiments show that the method proposed in this paper can effectively improve the recognition accuracy of fine-grained hand shape images and the result is consistent with the evaluation of professional advisors, which realizes the perfect combination of the intelligent image recognition and the hand shape evaluation for Chinese traditional instrument performing.     

A variable neighborhood search algorithm to generate piano fingerings for polyphonic sheet music

A piano fingering indicates which finger should play each note in a piece. Such a guideline is very helpful for both amateur and experienced players in order to play a piece fluently. In this paper, we propose a variable neighborhood search algorithm to generate piano fingerings for complex polyphonic music, a frequently encountered case that was ignored in previous research. The algorithm takes into account the biomechanical properties of the pianist's hand in order to generate a fingering that is user‐specific and as easy to play as possible. An extensive statistical analysis was carried out in order to tune the parameters of the algorithm and evaluate its performance. The results of computational experiments show that the algorithm generates good fingerings that are very similar to those published in sheet music books.     

音乐信息检索下的乐器识别综述

高效精准的乐器识别技术可以有效地推动声源分离、音乐识谱、音乐流派分类等研究的深入发展,可广泛应用于播放列表生成、声学环境分类、乐器智能教学和交互式多媒体等众多领域。近年来,随着乐器识别研究的不断推进,乐器识别系统在性能上有了大幅提高,但依旧存在着部分乐器难以识别、乐器音频特征提取较为困难、复音乐器识别精准度较低等诸多问题,如何借助人工智能技术对乐器进行高效精准的识别成为当前研究的热点和难点。针对当前研究现状,从乐器识别常用音频特征、乐器识别模型及方法和常用数据集三个方面进行综述,并对当前研究中存在的局限性和未来发展趋势进行总结,为乐器识别研究提供一定的借鉴参考。     

Intelligent and perceptual-based approach to musical instruments sound design

A novel, generic framework for musical instrument sound design is proposed. The framework uses an intelligent and perceptual based approach to address the two main problems in sound design - optimization of synthesis parameters and assessment of sound quality. A fuzzy model is used to capture and exploit knowledge of sound design from audio experts. A robust methodology, based on the ITU Perceptual Evaluation of Audio Quality (PEAQ) algorithm, is used for objective prediction of sound synthesis quality and sound quality assessment. The new framework makes it possible to automate the optimization of synthesis parameters. It also allows the designer to evaluate objectively, the perceptual impact of individual parameters on the final sound quality which is useful for benchmarking sound synthesis methods. The framework is generic and can be used for sound design for a wide range of musical instruments. We illustrate the use of the framework in pipe organ sound design. Results from this show that the new approach provides an important and useful alternative to existing methods.     

面向混合乐器音乐分析的稀疏特征提取方法

为了解决混合乐器音乐数据的成分识别与解析研究中,现有方法过度依赖数据标签,且往往基于单纯频域或物理特征,与乐器固有性质关联不明显、对复杂成分的敏感度不足的问题,提出了一种基于稀疏分解和多种乐器成分字典的稀疏特征提取方法,通过对稀疏系数向量进行深入分析,得到可以独立使用,具有高可解释性的稀疏音乐特征。实验结果证明,这种特征能够直观地反映乐器成分组成与音乐情绪的变化,在混合乐器成分分析和其他各类时变信号分析领域具有显著的应用价值。     

基于PoseC3D的网球动作识别及评价方法

为了准确地识别及评价网球动作,将计算机视觉与网球运动相关知识相结合,提出了一种基于PoseC3D的网球动作识别及评价方法。首先,使用基于ResNet-50姿态估计模型对网球运动视频进行人体目标检测并提取骨骼关键点;然后,使用在专业网球场采集的视频数据集进行PoseC3D模型训练,使模型能够对网球的子动作进行分类;之后,使用动态时间规整算法对分类的动作进行评价;最后,基于采集的视频数据集进行了大量实验。结果表明,提出的基于PoseC3D的网球动作识别方法对6类网球子动作的分类Top1准确率可以达到90.8%。相较于基于图卷积网络的方法,比如AGCN和ST-GCN,具有更强的泛化能力;提出的基于动态时间规整的评分算法能够在动作分类后实时、准确地给出相应动作的评价分数,从而减少了网球教师的工作强度,有效地提升了网球教学质量。     

WAVE: Sound and music in an immersive environment

This paper presents WAVE—a Virtual Audio Environment, which embraces the implementation of an immersive musical instrument model that uses three-dimensional (3D) sound techniques combined with visualisation and virtual reality technologies. This prototype environment aims to extend the idea of a musical instrument into a new musical/audio system, incorporating traditional musical concepts side by side with actual music concepts, in order to progress one step further in the music/sound composing and performing approaches.

The architecture of the system is based on low-cost hardware and open source software with affordable professional audio equipment to maintain an adequate sound quality. Also several applications of this virtual environment are discussed in the paper, including the way to satisfy at the same time composers, performers, music/audio students or even simple occasional users.     

CHORD RECOGNITION USING NEURAL NETWORKS BASED ON PARTICLE SWARM OPTIMIZATION

A sequence of musical chords can facilitate musicians in music arrangement and accompaniment. To implement an intelligent system for chord recognition, in this article we propose a novel approach using artificial neural networks (ANN) trained bythe particle swarm optimization (PSO) technique and back-propagation (BP) learning algorithm. All of the training and testing data are generated from musical instrument digital interface (MIDI) symbolic data. Furthermore, in order to improve the recognition efficiency, an additional feature of cadencesis included. In other words, cadence is not only the structural punctuation of a melodic phrase but is considered as the important feature for chord recognition. Experimental results of our proposed approach show that adding a cadence feature significantly improves recognition rate, and the ANN-PSO method outperforms ANN-BP in chord recognition. In addition, because preliminary experimental recognition rates are generally not stable enough, we chose the optimal ANNs to propose a two-phase ANN model to integrate the results among many models.     

视频大数据研究综述

科学技术与生产力的发展带来了数据量的高速增长,其中视频图像等多媒体数据占了很大的比重。如何高效处理这些海量数据并从中快速挖掘有价值的信息是当前的研究热点。通常大数据具有四个特点,即数据量大、需要快速响应、数据类型多样和价值密度低。视频大数据同样具有以上特点,但其特殊性在于数据冗余更大,需要进行高效的压缩编码与分析处理。总的来说,视频大数据的研究内容包括了视频数据表示、智能视频分析、视频压缩与传输、视频显示与评价等方面。在发展趋势上,视频数据的表示将向真实感与智能化两个方向发展;智能视频分析技术将会借助深度神经网络获得更准确的识别分类结果;视频压缩技术在提升压缩效率的同时也会探索降低编码复杂度的方法,并通过结合人眼视觉感知特性的编码算法来减少视频大数据的视觉冗余;视频显示设备将伴随着视频数据表示形式的改变而进行相应的升级换代;视频质量的评价准则将由单一的图像质量评价向更加综合全面的用户体验质量评价发展。     

基于人工智能的高职院校专业办学水平评估系统

以重庆工职院机械学院的国家示范建设重点专业"数控技术"为研究目标,给出了一个完善的校内自我评估模式,建立了相关的指标体系和质量标准.运用模糊神经网络的原理和方法,建立了基于FNN-ES的综合评价模型和基于VC++的评估软件具体实现,给出了使用人工评估的结果对智能模型进行训练和使用的详细过程.利用matlab验证和改善该FNN算法的性能,训练成熟的软件可用于校内成熟专业的评估,并进而推广到其它院校,理论和实践的结果表明,FNN-ES用于专业评估能克服各种人为因素,使评估结果更科学、稳定和合理,能为省级和国家级层面上的校外评估提供导向和基础数据.     

浅谈智能视频监控技术及其主要应用

在对智能视频监控技术内容和框架深入了解的基础上,对智能视频监控技术的主要结构进行了简要的介绍,同时针对智能视频监控系统中的关键技术进行了系统的分析,然后从安全相关类和非安全相关类2个方面对智能视频监控技术的应用层面进行了简要的阐述,最后提出了智能视频分析前端系统、三维全景多视角监控系统、视频警戒系统、视频图像甄别处理系统和高空瞭望监控系统5种智能视频监控应用系统。     

J2EE架构下智能视频检索系统集成框架研究

提出了一种基于J2EE平台的智能视频检索系统集成框架,并实现了具有视频分析、内容管理、基于WEB检索和浏览等功能的视频检索系统iVideo。该系统参照MPEG7标准描述视频数据,这种描述便于视频内容的管理;系统采取高层语义特征与底层视觉特征融合以及相关反馈等手段有效提高检索的准确度,并能根据不同的终端设备自适应地显示查询结果。     

轧制力在线智能监测虚拟仪器开发研究

本文介绍了一个利用虚拟仪器技术开发的轧制力在线智能监测系统。系统以PC工控机为主控平台,利用虚拟仪器开发软件LabVIEW7.1与使用PCI总线的高性能多通道数据采集卡相结合,实现对轧制力信号自动采集、判断、智能数据处理等功能。     

多现场总线接口智能仪表设计

在不同现场总线的产品共存的自动化系统中,如何使新兴智能仪表与原有现场设备或未来更新设备在通信方面相兼容,已经成为一个现实问题.为此,提出了智能仪表中多现场总线接口技术.从硬软件方面研究了智能仪表中MODBUS、PROFIBUS和CANBUS三种现场总线通信接口,重点分析了设计中的关键问题,并结合电工仪表产品实现了三种现...     

智能声发射仪的研究

针对现有的声发射仪仅具有声发射数据采集功能,而无数据分析处理功能的问题,提出了一种智能声发射仪的设计方案。该声发射仪在数字式声发射仪的基础上,通过建立已知缺陷模式库,采用模糊识别模式对活动缺陷进行类型判定并作出等级评估。下一步工作重点是建立一个比较完善的标准声发射源数据库,为仪器的智能化实现打下基础。     

基于深度时空残差卷积神经网络的课堂教学视频中多人课堂行为识别

针对课堂教学场景遮挡严重、学生众多,以及目前的视频行为识别算法并不适用于课堂教学场景,且尚无学生课堂行为的公开数据集的问题,构建了课堂教学视频库以及学生课堂行为库,提出了基于深度时空残差卷积神经网络的课堂教学视频中实时多人学生课堂行为识别算法.首先,结合实时目标检测和跟踪,得到每个学生的实时图片流;接着,利用深度时空残...     

Integrating gray system theory and logistic regression into case-based reasoning for safety assessment of thermal power plants

Safety assessment of thermal power plants (TPPs) is one of the important means to guarantee the safety of production in thermal power production enterprises. Due to various technical limitations, existing assessment approaches, such as analytic hierarchy process (AHP), Monte Carlo methods, artificial neural network (ANN), etc., are unable to meet the requirements of the complex security assessment of TPPs. Currently, most of the security assessments of TPP are completed by the means of experts’ evaluations. Accordingly, the assessment conclusions are greatly affected by the subjectivity of the experts. Essentially, the evaluation of power plant systems relies to a large extent on the knowledge and length of experience of the experts. Therefore in this domain case-based reasoning (CBR) is introduced for the security assessment of TPPs since this methodology models expertise through experience management. Taking the management system of TPPs as breakthrough point, this paper presents a case-based approach for the Safety assessment decision support of TPPs (SATPP). First, this paper reviews commonly used approaches for TPPs security assessment and the current general evaluation process of TPPs security assessment. Then a framework for the Management System Safety Assessment of Thermal Power Plants (MSSATPP) is constructed and an intelligent decision support system for MSSATPP (IDSS-MSSATPP) is functionally designed. IDSS-MSSATPP involves several key technologies and methods such as knowledge representation and case matching. A novel case matching method named Improved Gray CBR (IGCBR) has been developed in which a statistical approach (logistic regression) and Gray System theory are integrated. Instead of applying Gray System theory directly, it has been improved to integrate it better into CBR. In addition this paper describes an experimental prototype system of IDSS-MSSATPP (CBRsys-TPP) in which IGCBR is integrated. The experimental results based on a MSSATPP data set show that CBRsys-TPP has high accuracy and systematically good performance. Further comparative studies with several other common classification approaches also show its competitive power in terms of accuracy and the synergistic effects of the integrated components.     

基于模糊理论的智能呼叫决策系统的研究与设计

针对呼叫系统中接入控制的决策问题,从影响呼叫客户重要性的四个因素出发,构造了客户重要程度评估集,并提出了在呼叫系统中基于模糊综合评判的呼叫评估方法及相关算法实现,较好地解决了处理客户呼叫的问题,然后设计了智能呼叫决策系统,最后通过与非智能化系统的损失量比较,验证了该智能决策系统的有效性和可行性。     

Low-Power Content-Based Video Acquisition for Super-Resolution Enhancement

Motivated by the optimization of power and improvement of video resolution, this paper proposes a content-based adaptive sampling system for video acquisition. Blind sampling suffers from the lack of resolution and blurring. However, use of À priori knowledge can provide intelligent sampling function that will reduce the blur artifacts. This paper proposes an information theoretic criteria-based sampling function. Higher sampling is proposed at high motion and edge regions while lower sampling at the low-frequency regions. This helps in providing better resolution with lower power consumption. Previous researches focus on enhancing the coding performance after the video acquisition stage. The proposed adaptive sampling scheme naturally performs super resolution without requiring extensive postprocessing. The proposed scheme has been tested on ten exemplary video sequences. Quality of the proposed adaptive sampling method is over 10–16 dB better than the coarsely sampled video. The power savings is ${approx}30hbox{--}40hbox{%}$ compared to acquiring the full resolution video.