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Development of online classification system for construction waste based on industrial camera and hyperspectral camera

机译:基于工业相机和高光谱相机的建筑垃圾在线分类系统的开发

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摘要

Construction waste is a serious problem that should be addressed to protect environment and save resources, some of which have a high recovery value. To efficiently recover construction waste, an online classification system is developed using an industrial near-infrared hyperspectral camera. This system uses the industrial camera to capture a region of interest and a hyperspectral camera to obtain the spectral information about objects corresponding to the region of interest. The spectral information is then used to build classification models based on extreme learning machine and resemblance discriminant analysis. To further improve this system, an online particle swarm optimization extreme learning machine is developed. The results indicate that if a near-infrared hyperspectral camera is used in conjunction with an industrial camera, construction waste can be efficiently classified. Therefore, extreme learning machine and resemblance discriminant analysis can be used to classify construction waste. Particle swarm optimization can be used to further enhance the proposed system.
机译:建筑废料是一个严重的问题,应该解决以保护环境和节省资源,其中一些具有很高的回收价值。为了有效地回收建筑垃圾,使用工业近红外高光谱相机开发了在线分类系统。该系统使用工业相机捕获关注区域,并使用高光谱相机获取有关与该关注区域相对应的对象的光谱信息。然后将光谱信息用于基于极限学习机和相似度判别分析的分类模型。为了进一步完善该系统,开发了在线粒子群优化极限学习机。结果表明,如果将近红外高光谱相机与工业相机结合使用,则可以有效地分类建筑垃圾。因此,极限学​​习机和相似度判别分析可用于对建筑垃圾进行分类。粒子群优化可用于进一步增强建议的系统。

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