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This research proposes a comprehensive framework for clothing waste segregation and management, integrating computer vision and machine learning. The methodology involves collecting diverse clothing waste images, preprocessing data for quality enhancement, and utilizing computer vision techniques, such as segmentation and object detection. Machine learning models, including transfer learning, dynamically adapt to evolving fashion trends. The integration framework ensures seamless interaction between computer vision and machine learning, guiding accurate classification and routing designated clothing waste for re-manufacturing. Continuous monitoring and optimization, guided by predefined metrics, contribute to iterative improvements, enhancing the system's adaptability to emerging trends for sustainable clothing waste management.

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A Scope of Investigation into the Integration of Computer Vision and Machine Learning for Clothing Waste Segregation and Management Using AI

  • 会议论文

  • 发表日期：

    2025年

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  • Gujjula Anjareddy,
  • Bimmarolu Shanthi,
  • Renuka Kuntala,
  • K. Venkata Balamurali Krishna,
  • Peddi Niranjan Reddy,
  • Mruthyunjayam Allakonda

摘要

This research proposes a comprehensive framework for clothing waste segregation and management, integrating computer vision and machine learning. The methodology involves collecting diverse clothing waste images, preprocessing data for quality enhancement, and utilizing computer vision techniques, such as segmentation and object detection. Machine learning models, including transfer learning, dynamically adapt to evolving fashion trends. The integration framework ensures seamless interaction between computer vision and machine learning, guiding accurate classification and routing designated clothing waste for re-manufacturing. Continuous monitoring and optimization, guided by predefined metrics, contribute to iterative improvements, enhancing the system's adaptability to emerging trends for sustainable clothing waste management.