Construction of Intelligent Recognition and Learning Education Platform of National Music Genre Under Deep Learning

Xu, Zhongkui

doi:10.3389/fpsyg.2022.843427

Cited by 8 publications

(5 citation statements)

References 36 publications

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“…Deep learning approaches, notably CNNs, have been used for a range of computer vision problems with state-of-the-art outcomes. Image classification [20], object recognition [21]and biomedical image segmentation [12] are just a few examples. CNN has the potential to understand in a hierarchical order of progressively complicated features directly from data.…”

Section: Cascaded Approach For Tumor Segmentationmentioning

confidence: 99%

Revolutionizing Brain Tumor Segmentation in MRI with Dynamic Fusion of Handcrafted Features and Global Pathway-based Deep Learning

2024

KSII TIIS

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Gliomas are the most common malignant brain tumor and cause the most deaths. Manual brain tumor segmentation is expensive, time-consuming, error-prone, and dependent on the radiologist's expertise and experience. Manual brain tumor segmentation outcomes by different radiologists for the same patient may differ. Thus, more robust, and dependable methods are needed. Medical imaging researchers produced numerous semi-automatic and fully automatic brain tumor segmentation algorithms using ML pipelines and accurate (handcrafted feature-based, etc.) or data-driven strategies. Current methods use CNN or handmade features such symmetry analysis, alignment-based features analysis, or textural qualities. CNN approaches provide unsupervised features, while manual features model domain knowledge. Cascaded algorithms may outperform feature-based or data-driven like CNN methods. A revolutionary cascaded strategy is presented that intelligently supplies CNN with past information from handmade feature-based ML algorithms. Each patient receives manual ground truth and four MRI modalities (T1, T1c, T2, and FLAIR). Handcrafted characteristics and deep learning are used to segment brain tumors in a Global Convolutional Neural Network (GCNN). The proposed GCNN architecture with two parallel CNNs, CSPathways CNN (CSPCNN) and MRI Pathways CNN (MRIPCNN), segmented BraTS brain tumors with high accuracy. The proposed model achieved a Dice score of 87% higher than the state of the art. This research could improve brain tumor segmentation, helping clinicians diagnose and treat patients.

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Section: Cascaded Approach For Tumor Segmentationmentioning

confidence: 99%

Revolutionizing Brain Tumor Segmentation in MRI with Dynamic Fusion of Handcrafted Features and Global Pathway-based Deep Learning

2024

KSII TIIS

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“…This process should take into account that the typical sound source of five-element music therapy is mainly based on oriental instrumental music. One recent study attempted to extract the characteristic parameters of traditional Chinese instrumental music with the mel frequency cepstral coefficient [25]. This case can also be considered for the characterization of five-element music therapy.…”

Section: Not Specifiedmentioning

confidence: 99%

The Modernization of Oriental Music Therapy: Five-Element Music Therapy Combined with Artificial Intelligence

Kwon,

Kim,

Kim

2024

Healthcare

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In recent years, music has been regarded as a promising non-pharmacological intervention for a number of physical and mental conditions. Five-elements music therapy—based on the five-element theory—is a unique non-pharmacological therapy of East Asian traditional medicine. It has the potential to effectively provide individualized music therapy to individuals with illness. However, one limitation of this music therapy is that the classification of the five elements and its application is mainly based on subjective judgment. The development of artificial intelligence (AI) has enabled the acoustic analysis of multi-factor sound sources. This can develop five-element music therapy. Here, we discussed the challenges proposed by the future combination of five-element music therapy and AI. Further, we hypothesized that AI may promote its use in the medical field.

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“…Manco et al (2021) propose to address music description via audio captioning, defined as the task of generating a natural language description of music audio content in a human-like manner. In order to study the application of the deep-learning method in music-genre recognition, Xu (2022) proposes the parameter-extraction feature and the recognition-classification method of an ethnic music genre based on the deep beliefs network (DBN) with five kinds of ethnic musical instruments as the experimental objects. The DBN is the best way for softmax to identify and classify national musical…”

Section: Related Workmentioning

confidence: 99%

Construction and Implementation of Content-Based National Music Retrieval Model Under Deep Learning

Shi,

Liu

2024

International Journal of Information System Modeling and Design

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This research mainly studies the construction and implementation of the content-based folk music retrieval model. Firstly, it studies the music automatic annotation method based on deep learning, and then proposes the tag conditional random field music automatic annotation method, and then constructs the music annotation depth neural network model combining a variety of music representation and attention mechanism. Finally, it analyzes the proposed folk music retrieval model the effectiveness of the cable model is verified and its performance is evaluated. The results show that in Glu module, Glu blocks had better performance in music annotation, and the music annotation results of each index in music hierarchical sequence modeling are better, which ensures the effectiveness of music annotation. Compared with other algorithms, the AUC tag score of the proposed method is the highest, which is 0.913; it can better model the mapping relationship between the audio features of music input to the text tag and has higher scores on all evaluation indicators.

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Construction of Intelligent Recognition and Learning Education Platform of National Music Genre Under Deep Learning

Cited by 8 publications

References 36 publications

Revolutionizing Brain Tumor Segmentation in MRI with Dynamic Fusion of Handcrafted Features and Global Pathway-based Deep Learning

Revolutionizing Brain Tumor Segmentation in MRI with Dynamic Fusion of Handcrafted Features and Global Pathway-based Deep Learning

The Modernization of Oriental Music Therapy: Five-Element Music Therapy Combined with Artificial Intelligence

Construction and Implementation of Content-Based National Music Retrieval Model Under Deep Learning

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