Work

Recognition of Plastic Bottles Region Using Improved DeepLab v3+

Year: 2025

Type: conference-paper

Abstract: Factory automation is one solution to the labor shortage.We focus on the sorting of plastic bottles in waste disposal plants and try to automate the process using robotic arms.In this paper, we propose an image analysis method for the recognition of plastic bottles limited to 500ml capacity.The method is semantic segmentation, and the deep learning model is DeepLab v3+.Modifications using ECA Block and Mish function show improvements at the points of misrecognition with the base model.

Source: Proceedings of International Conference on Artificial Life and Robotics

DOI: 10.5954/icarob.2025.gs2-1

Authors: Yusuke Murata, Tohru Kamiya

Institution: Kyushu Institute of Technology

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Responsible consumption and production

Open Access status: bronze

OpenAlex ID: W4409913639