International Journal Of Imaging

Abstract

SMART WASTE MANAGEMENT SYSTEM LEVERAGING DEEP LEARNING TECHNIQUES TO CLASSIFY WASTE TYPES FOR OPTIMAL RECYCLING AND DISPOSAL

Author: Girirajula Jai Shree, Yeluri Harika, Govuri Tejaswini, Dr. Ch. Srikanth

Abstract:

The need to distinguish between organic and non-organic images has gained prominence in various fields due to its significant implications for automating processes and decision-making. Conventional systems for organic and non-organic image classification typically involve the design of rule-based or feature-engineered algorithms, often based on colour, texture, or shape features. These approaches have several drawbacks. Firstly, they require substantial domain knowledge and manual feature extraction, making them labour-intensive and prone to human bias. Secondly, they may not handle the inherent variations and complexities in real-world images, as objects or scenes can exhibit diverse characteristics. Additionally, these systems tend to struggle with generalization to unseen data and often necessitate frequent re-engineering for adapting to evolving image categories. The proposed deep learning model represents a breakthrough in organic and non-organic image classification. It ut