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This research presents a thorough comparison of three popular deep learning models: EfficientNetB3, MobileNetV2, and ResNet50, for its performance using synthetic dataset. The models are used on a dataset of artificial images that depicts plastic, paper, and trash bags. The goal of the research is to provide useful insights for practical applications while exposing the models’ advantages and disadvantages in artificial image data. Precise picture classification is applied in agriculture, recycling, and health care, improving agricultural production, waste management effectiveness, and medical diagnosis. This work advances the field of computer vision and provides experts in a variety of industries with useful advice.

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Comparative Analysis of Deep Learning Models for Image Classification: A Study on Synthetic Images of Bags

  • 会议论文

  • 发表日期：

    2025年

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  • Dhwanil Chauhan,
  • Sachin Patel,
  • Margi Shah,
  • Twisha Patel,
  • Sujal Sutariya,
  • Ankur Patel,
  • Diya Patel,
  • Isha Patel

摘要

This research presents a thorough comparison of three popular deep learning models: EfficientNetB3, MobileNetV2, and ResNet50, for its performance using synthetic dataset. The models are used on a dataset of artificial images that depicts plastic, paper, and trash bags. The goal of the research is to provide useful insights for practical applications while exposing the models’ advantages and disadvantages in artificial image data. Precise picture classification is applied in agriculture, recycling, and health care, improving agricultural production, waste management effectiveness, and medical diagnosis. This work advances the field of computer vision and provides experts in a variety of industries with useful advice.