I. J. of Electrical & Electronics Research
Research Article | 
Automatic Framework for Vegetable Classification using Transfer-Learning
Author(s) : Harendra Singh1, Roop Singh2, Parul Goel3, Anil Singh4 and Naveen Sharma5
Published In : International Journal of Electrical and Electronics Research (IJEER) Volume 10, Issue 2
Publisher : FOREX Publication
Published : 30 June 2022
e-ISSN : 2347-470X
Page(s) : 405-410
Abstract
Globally, fresh vegetables are a crucial part of our lives and they provide most of the vitamins, minerals, and proteins, in short, every nutrition that a growing body need. They vary in colors like; red, green, and yellow but as our ancestors say that green vegetables are a must for every age. To identify the fresh vegetable that makes our body healthy and notion positive the proposed automatic multi-class vegetable classifier is used. In this paper, a framework based on a deep learning approach has been proposed for multi-class vegetable classification from scratch. The accuracy of the proposed model is further increased using the transfer-learning concept (DenseNet201). The whole process is divided into four modules; data collection and pre-processing, data splitting, CNN model training, and testing, and performance improvement using a pre-trained DenseNet201 network. Data augmentation and data shuffling are used to free from lack of data availability during the training phase of the model. The proposed framework is more efficient and can predict the type of vegetables comparatively in less computational time (2 to 3 minutes) with an ‘Accuracy’ of 98.58%, ‘Sensitivity’ of 98.23%, and ‘Specificity’ of 94.25%.
Keywords: Convolution Neural Network (CNN), Data Augmentation and shuffling, Transfer learning (DenseNet201)
Harendra Singh, Assistant Professor, G. L. Bajaj Institute of Technology and Management, Greater Noida, India
Roop Singh, Biomedical Applications, CSIR-Central Scientific Instrumentations Organization, Sector-30C, Chandigarh-160030, India; Email: roopsolanki@gmail.com
Parul Goel, Assistant Professor, G. L. Bajaj Institute of Technology and Management, Greater Noida, India
Anil Singh, Associate Professor, Arni University, Kathgarh Indora Himachal Pradesh, India
Naveen Sharma, Biomedical Applications, CSIR-Central Scientific Instrumentations Organization, Sector-30C, Chandigarh-160030, India
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Harendra Singh, Roop Singh, Parul Goel, Anil Singh and Naveen Sharma (2022), Automatic Framework for Vegetable Classification using Transfer-Learning. IJEER 10(2), 405-410. DOI: 10.37391/IJEER.100257.