Work

Deep Learning Based Integrated Removable Smart Waste Sorting Device

Year: 2025

Type: conference-paper

Abstract: In this study, an intelligent waste sorting device based on Inception v3 and migration learning is developed to achieve fast and accurate waste recognition and sorting through deep learning and sensor fusion techniques.The device is designed to be detachable and adaptable to existing bins, with the ability to continuously learn new waste types.Through real-time data transmission, the device supports remote monitoring and management, which effectively improves the efficiency of waste classification and is important for urban environmental protection.

Source: Proceedings of International Conference on Artificial Life and Robotics

DOI: 10.5954/icarob.2025.os10-7

Authors: Yanhong Yu, Liangyu Wang, Yizhun Peng

Institution: Tianjin University of Science and Technology

Language: English

Topic: Advanced Neural Network Applications

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDGs: Responsible consumption and production, Industry, innovation and infrastructure

Open Access status: bronze

OpenAlex ID: W4409914136