A simple and efficient deep learning-based framework for vegetable recognition

Xian Gong

doi:10.1117/12.3000777

9 August 2023 A simple and efficient deep learning-based framework for vegetable recognition

Xian Gong

Proceedings Volume 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023); 127821B (2023) https://doi.org/10.1117/12.3000777
Event: Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Since the 21st century, artificial intelligence has been continuously evolving in various fields, particularly in agriculture. Vegetables, as a critical component of agriculture and human diets, have always been a focal point in terms of cultivation, production, and sales. Compared to traditional vegetable classification that requires professional knowledge and experience, AI technology utilizes computer vision to achieve automated classification. This study presents a deep learning-based vegetable recognition system aimed at automating the identification and classification of vegetables. The system utilizes a convolutional neural network (CNN) as its fundamental algorithm, integrating the traditional CNN architecture, which comprises convolutional layers, pooling layers, and fully connected layers. In comparison to other vegetable recognition systems on the market, this system utilizes a simpler architecture for processing and classifying vegetable images, significantly improving the accuracy and compatibility of identification. The research steps comprise data collection, image preprocessing, model training, and model testing. Experimental results demonstrate that the system can rapidly and accurately identify and classify various vegetables, with an average accuracy rate exceeding 95% on the test dataset, showcasing high practical value.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xian Gong "A simple and efficient deep learning-based framework for vegetable recognition", Proc. SPIE 12782, Third International Conference on Image Processing and Intelligent Control (IPIC 2023), 127821B (9 August 2023); https://doi.org/10.1117/12.3000777

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KEYWORDS

Data modeling

Education and training

Image processing

Deep learning

Convolution

Convolutional neural networks

System identification

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