典型文献
New Benchmark for Household Garbage Image Recognition
文献摘要：
Household garbage images are usually faced with complex backgrounds,variable illuminations,diverse angles,and changeable shapes,which bring a great difficulty in garbage image classification.Due to the ability to discover problem-specific features,deep learning and especially convolutional neural networks(CNNs)have been successfully and widely used for image representation learning.However,available and stable household garbage datasets are insufficient,which seriously limits the development of research and application.Besides,the state-of-the-art in the field of garbage image classification is not entirely clear.To solve this problem,in this study,we built a new open benchmark dataset for household garbage image classification by simulating different lightings,backgrounds,angles,and shapes.This dataset is named 30 classes of household garbage images(HGI-30),which contains 18 000 images of 30 household garbage classes.The publicly available HGI-30 dataset allows researchers to develop accurate and robust methods for household garbage recognition.We also conducted experiments and performance analyses of the state-of-the-art deep CNN methods on HGI-30,which serves as baseline results on this benchmark.
文献关键词：
中图分类号：
作者姓名：
Zhize Wu;Huanyi Li;Xiaofeng Wang;Zijun Wu;Le Zou;Lixiang Xu;Ming Tan
作者机构：
School of Artificial Intelligence and Big Data,Hefei University,Hefei 230601,China;School of Energy Materials and Chemical Engineering,Hefei University,Hefei 230601,China
文献出处：
引用格式：
[1]Zhize Wu;Huanyi Li;Xiaofeng Wang;Zijun Wu;Le Zou;Lixiang Xu;Ming Tan-.New Benchmark for Household Garbage Image Recognition)[J].清华大学学报自然科学版（英文版）,2022(05):793-803
A类：
lightings
B类：
New,Benchmark,Household,Garbage,Image,Recognition,garbage,images,are,usually,faced,complex,backgrounds,variable,illuminations,diverse,angles,changeable,shapes,which,bring,great,difficulty,classification,Due,ability,discover,problem,specific,features,deep,learning,especially,convolutional,neural,networks,CNNs,have,been,successfully,widely,used,representation,However,available,stable,household,datasets,insufficient,seriously,limits,development,application,Besides,state,art,field,not,entirely,clear,To,solve,this,study,built,new,open,benchmark,by,simulating,different,This,named,classes,HGI,contains,publicly,allows,researchers,accurate,robust,methods,recognition,We,also,conducted,experiments,performance,analyses,serves,baseline,results
AB值：
0.562228
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机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
