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  • 青岛科技大学

杨树国

基于数学建模的“三轴联动、五层递进”研究生创新能力培养模式的研究与实践 -----第九届山东省省级教学成果奖佐证材料一、成果曾获奖励二、团队主要成员指导研究生数学建模竞赛获奖统计三、我校连续12年获“中国研究生数学建模竞赛优秀组织奖”荣誉称号四、团队主要成员获批教研项目五、团队主要成员获批课程立项六、团队主要成员的教学论文和教材七、成果推广应用证明

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Image double encryption method based on chaotic map and DWT

发布时间:2023-10-19 点击次数:

  • 关键字:NEURAL-NETWORKS; CLASSIFICATION
  • 摘要:Polyphonic sound event detection aims to detect the types of sound events that occur in given audio clips, and their onset and offset times, in which multiple sound events may occur simultaneously. Deep learning-based methods such as convolutional neural networks (CNN) achieved state-of-the-art results in polyphonic sound event detection. However, two open challenges still remain: overlap between events and prone to overfitting problem. To solve the above two problems, we proposed a capsule network-based method for polyphonic sound event detection. With so-called dynamic routing, capsule networks have the advantage of handling overlapping objects and the generalization ability to reduce overfitting. However, dynamic routing also greatly slows down the training process. In order to speed up the training process, we propose a weakly labeled polyphonic sound event detection model based on the improved capsule routing. Our proposed method is evaluated on task 4 of the DCASE 2017 challenge and compared with several baselines, demonstrating competitive results in terms of F-score and computational efficiency.
  • 卷号:2022
  • 期号:1
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