计算机科学
鉴别器
人工智能
卷积(计算机科学)
目标检测
卷积神经网络
深度学习
过程(计算)
发电机(电路理论)
对象(语法)
计算
人工神经网络
图像(数学)
视觉对象识别的认知神经科学
计算机视觉
生成对抗网络
模式识别(心理学)
算法
电信
功率(物理)
物理
量子力学
探测器
操作系统
作者
Christine Dewi,Rung-Ching Chen,Hendry Hendry,Yanting Liu
标识
DOI:10.1109/icawst.2019.8923404
摘要
Object detection and image recognition are important research topics in machine learning and artificial intelligence. The major challenge of the computer vision image recognition is to detect and recognize a similar object. Generative Adversarial Network (GAN) based on Convolution Neural Network (CNN) is proposed to faces this challenge. The advantage of the GAN is represented by its architecture which consists of a generator and discriminator to detect real or fake image generated by the machine. In this paper, we adopt the advantage of GAN and combine with YOLO algorithm to identify similar music instruments. YOLO is fast Region based CNN with powerful computation. Using Deep Convolution YOLO-GAN will enhance the capability of YOLO detection process and outperform the original YOLO capability.
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