Journal
INTELLIGENT SUSTAINABLE SYSTEMS, WORLDS4 2022, VOL 2
Volume 579, Issue -, Pages 483-493Publisher
SPRINGER-VERLAG SINGAPORE PTE LTD
DOI: 10.1007/978-981-19-7663-6_46
Keywords
Deep learning; Radish; ResNet; MobileNet; VGG16; VGG19; Freshness
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This paper discusses the application of deep learning and computer vision in automating freshness classification. It demonstrates the effectiveness of these new technologies in improving accuracy and efficiency compared to manual labor methods.
Automation of freshness classification is an application of Deep learning and Computer Vision. Normal methods are manual labor which are time-consuming and inefficient. In recent years many new technologies come into place like deep learning and computer vision, since the shape is the main freshness classification, these new technologies are proved to be very useful, since the process has been improved in the terms of both accuracy and time. This paper consists of various image processing techniques used for Radish freshness classification. Comparison among different models has been made on the bases of training and testing accuracy.
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