Relabeling Method for Improving Vehicle Part Detection

Hong, Sung‐Jin; Yu, ChoRong; Gil, Youn-Hee; Shin, Hee Sook; Baek, Seong Min

doi:10.1109/ictc55196.2022.9952827

Cited by 2 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In industrial part classification, Hong et al introduced a method to relabel the detection result of vehicle parts [29]. Prasad et al proposed a novel deep learning approach to classify the various parts of any operational engine; it can qualitatively classify and henceforth give the corresponding class label of the machinery/engine part under consideration [30].…”

Section: Industrial Part Classificationmentioning

confidence: 99%

See 1 more Smart Citation

A DenseNet‐based feature weighting convolutional network recognition model and its application in industrial part classification

An,

Sun,

Song

et al. 2023

IET Image Processing

View full text Add to dashboard Cite

Traditional warehousing typically needs machine learning or manual tagging to classify objects. However, this method is less robust and consumes a lot of labour and material resources. Based on DenseNet, this work proposes a feature weighting convolutional network recognition model and designs a set of software and hardware for data acquisition, which is applied to the efficient classification of industrial parts in warehouse management. Firstly, this work modifies DenseNet by embedding SE‐Block, and replaces the cross‐entropy loss function with the focus loss function to optimize the model structure. Secondly, a multi‐view hardware and software acquisition system is designed to complete the functions of part image acquisition, image preprocessing, model training and part recognition. Finally, an industrial parts sorting experiment was designed. Compared with the original DenseNet model, the proposed weighted convolutional network identification model showed that the accuracy of the modified model was increased by 3.09% and the convergence rate was significantly improved. The modified model proposed in this work aims to improve the recognition accuracy of industrial parts in modern warehouse management, so as to modify the classification efficiency of warehouse parts in production.

show abstract

Section: Industrial Part Classificationmentioning

confidence: 99%

“…In industrial part classification, Hong et al. introduced a method to relabel the detection result of vehicle parts [29]. Prasad et al.…”

Section: Related Workmentioning

confidence: 99%