Survey on Real Time Fruit Detection and Classification using Image Processing and Convolution Neural Network

  • Unique Paper ID: 154581
  • Volume: 8
  • Issue: 11
  • PageNo: 617-622
  • Abstract:
  • Fruit classification is an important task for many industrial applications. Image recognition and classification using Convolution Neural Networks (CNN) are the two popular approaches used in object recognition systems. The advancements in deep learning-based models make it possible to recognize complex images. This paper proposes an efficient CNN based method that performs fruit recognition, Raw-Ripe classification, calorie estimation and provide the count of the fruits from an input image. Machine learning model needs to be trained using data-sets. The data-set used are various image data containing different variety of fruit.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{154581,
        author = {Charan G and Ganesh P and Dheeraj M S and Dr. P N Sudha},
        title = {Survey on Real Time Fruit Detection and Classification using Image Processing and Convolution Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {11},
        pages = {617-622},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154581},
        abstract = {Fruit classification is an important task for many industrial applications. Image recognition and classification using Convolution Neural Networks (CNN) are the two popular approaches used in object recognition systems. The advancements in deep learning-based models make it possible to recognize complex images. This paper proposes an efficient CNN based method that performs fruit recognition, Raw-Ripe classification, calorie estimation and provide the count of the fruits from an input image. Machine learning model needs to be trained using data-sets. The data-set used are various image data containing different variety of fruit. },
        keywords = {Fruit Classification, Calorie Estimation, Convolution Neural Network (CNN), Deep learning, Raspberry pi, YOLO V4, Image Processing, Image Segmentation},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 8
  • Issue: 11
  • PageNo: 617-622

Survey on Real Time Fruit Detection and Classification using Image Processing and Convolution Neural Network

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