Deep Learning Approaches for Evaluating the Quality of Fruits and Vegetables

The Fresh Fruit Identification Systemconstitutes a notable advancement in the meals industry. Employing sophisticated technologies along with machine-getting-to-know and computer imagination and prescient, it complements the great evaluation and optimization of perishable items, mainly focusing on culmination and greens. This contemporary system employs advanced gadgets gaining knowledge of models, especially convolutional neural networks (CNNs), to meticulously analyze high-decision pics of processed meals. By rapidly and appropriately identifying objects based totally on attributes that include shade, texture, and shape, the machine guarantees no longer the simplest precision in categorization but also an in-intensity best evaluation. This entails defect detection and ripeness assessment, ensuring that the most effective rate-satisfactory merchandise reaches customers. Implementing sturdy and scalable systems has addressed demanding situations associated with facts, model education, and real-time processing. Consequently, the Fresh Food Identification System emerges as a pivotal contributor to raising the standards of the perishable meals supply chain, embodying a dedication to excellence and performance.

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Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icetems64039.2024.10964979
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
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article

Deep Learning Approaches for Evaluating the Quality of Fruits and Vegetables

Gaurav Divtelwar, Dhananjay Bhagat, Aparna Bondade, Sandhya Patil et al.
Spectroscopy and Chemometric Analyses
article

Deep Learning Approaches for Evaluating the Quality of Fruits and Vegetables

Gaurav Divtelwar, Dhananjay Bhagat, Aparna Bondade, Sandhya Patil, Charvi Suri
article en

Abstract

The Fresh Fruit Identification Systemconstitutes a notable advancement in the meals industry. Employing sophisticated technologies along with machine-getting-to-know and computer imagination and prescient, it complements the great evaluation and optimization of perishable items, mainly focusing on culmination and greens. This contemporary system employs advanced gadgets gaining knowledge of models, especially convolutional neural networks (CNNs), to meticulously analyze high-decision pics of processed meals. By rapidly and appropriately identifying objects based totally on attributes that include shade, texture, and shape, the machine guarantees no longer the simplest precision in categorization but also an in-intensity best evaluation. This entails defect detection and ripeness assessment, ensuring that the most effective rate-satisfactory merchandise reaches customers. Implementing sturdy and scalable systems has addressed demanding situations associated with facts, model education, and real-time processing. Consequently, the Fresh Food Identification System emerges as a pivotal contributor to raising the standards of the perishable meals supply chain, embodying a dedication to excellence and performance.

MIT World Peace University (IN)
Zero hunger
Openalex Percentile: Top 73%
Spectroscopy and Chemometric Analyses
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