Combination of Resnet and Spatial Pyramid Pooling for Musical Instrument Identification

IF 1.2 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Christine Dewi, Rung-Ching Chen
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引用次数: 7

Abstract

Abstract Identifying similar objects is one of the most challenging tasks in computer vision image recognition. The following musical instruments will be recognized in this study: French horn, harp, recorder, bassoon, cello, clarinet, erhu, guitar saxophone, trumpet, and violin. Numerous musical instruments are identical in size, form, and sound. Further, our works combine Resnet 50 with Spatial Pyramid Pooling (SPP) to identify musical instruments that are similar to one another. Next, the Resnet 50 and Resnet 50 SPP model evaluation performance includes the Floating-Point Operations (FLOPS), detection time, mAP, and IoU. Our work can increase the detection performance of musical instruments similar to one another. The method we propose, Resnet 50 SPP, shows the highest average accuracy of 84.64% compared to the results of previous studies.
结合Resnet和空间金字塔池进行乐器识别
摘要识别相似物体是计算机视觉图像识别中最具挑战性的任务之一。以下乐器将在本研究中得到认可:法国圆号、竖琴、录音机、巴松管、大提琴、单簧管、二胡、吉他萨克斯管、小号和小提琴。许多乐器在大小、形式和声音上都是相同的。此外,我们的作品将Resnet 50与空间金字塔池(SPP)相结合,以识别彼此相似的乐器。接下来,Resnet 50和Resnet 50 SPP模型评估性能包括浮点运算(FLOPS)、检测时间、mAP和IoU。我们的工作可以提高彼此相似的乐器的检测性能。与之前的研究结果相比,我们提出的方法Resnet 50 SPP显示出84.64%的最高平均准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cybernetics and Information Technologies
Cybernetics and Information Technologies COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.20
自引率
25.00%
发文量
35
审稿时长
12 weeks
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