A multi-label waste detection model based on transfer learning
Author:
Publisher
Elsevier BV
Subject
Economics and Econometrics,Waste Management and Disposal
Reference50 articles.
1. Adedeji, O., & Wang, Z. (2019). Intelligent waste classification system using deep learning convolutional neural network. Procedia Manuf., 35, 607–612. 10.1016/j.promfg.2019.05.086.
2. Aral, R.A., Keskin, Ş.R., Kaya, M., & Hacıömeroğlu, M. (2018). Classification of trashnet dataset based on deep learning models. Paper presented at the 2018 IEEE International Conference on Big Data (Big Data). 10.1109/BigData.2018.8622212.
3. Bircanoğlu, C., Atay, M., Beşer, F., Genç, Ö., & Kızrak, M.A. (2018). RecycleNet: intelligent waste sorting using deep neural networks. Paper presented at the 2018 Innovations in Intelligent Systems and Applications (INISTA). 10.1109/INISTA.2018.8466276.
4. AP-loss for accurate one-stage object detection;Chen;IEEE Trans. Pattern Anal. Mach. Intell,2020
5. Ciregan, D., Meier, U., & Schmidhuber, J. (2012). Multi-column deep neural networks for image classification. Paper presented at the 2012 IEEE Conference on Computer Vision and Pattern Recognition. 10.1109/CVPR.2012.6248110.
Cited by 40 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Optimization of automated garbage recognition model based on ResNet-50 and weakly supervised CNN for sustainable urban development;Alexandria Engineering Journal;2024-12
2. Optimization-driven artificial intelligence-enhanced municipal waste classification system for disaster waste management;Engineering Applications of Artificial Intelligence;2024-07
3. Multiple object characterization of recyclable domestic waste using binocular stereo vision;Instrumentation Science & Technology;2024-06-26
4. Qualitative classification of waste garments for textile recycling based on machine vision and attention mechanisms;Waste Management;2024-06
5. Low-Cost Recognition of Plastic Waste Using Deep Learning and a Multi-Spectral Near-Infrared Sensor;Sensors;2024-04-28
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3