SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification.

ABSTRACT: Waste management handles all kinds of waste, including household, industrial, municipal, organic, biomedical, biological, and radioactive wastes. People still face challenges in proper disposal methods for different types of waste, including landfill-bound items, recyclable materials, and biodegradable waste. Inadequate waste management poses a significant and multifaceted global challenge. The conventional method of segregating waste is a time-consuming and ineffective method that wastes human power and money. To address this issue in real time, sophisticated and sustainable waste management systems need to be implemented. The latest advancements in computer vision and deep learning offer efficient solutions for effective recycling and waste management. Existing deep learning models exhib

SUBMITTER: Madhavi B 

PROVIDER: S-EPMC11889143 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature