TY - GEN
T1 - Automated Sorting, Grading of Fruits Based on Internal and External Quality Assessment Using HSI, Deep CNN
AU - Rahul Ganesh, P.
AU - Priyatharshini, R.
AU - Sarath Kumar, M.
AU - Raj Kumar, A.
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Good quality fruits demand is expanding due to the ascent in the crowd. Gross domestic product of the multitudinous nations depends upon its export export plays a significant role in GDP. After harvesting they're washed, sorted, graded, pressed, and put down. Out of every one of these stages grading and sorting of fruits are vital way. The main end is to plan an automated system that improves the standard, upgrades the creation productivity, decreases the work cost of the fashion, and assesses the internal quality of the fruits. As per the agricultural and food products export development authority pomegranates, mangoes, bananas, papayas, and orange account for the larger portion of fruits exported from our country. Effective discovery is achieved using hyperspectral imaging, CNN frame. Superior performance than treating, sorting, and grading grounded on redundant classes in the CNN frame through the proposed architecture.
AB - Good quality fruits demand is expanding due to the ascent in the crowd. Gross domestic product of the multitudinous nations depends upon its export export plays a significant role in GDP. After harvesting they're washed, sorted, graded, pressed, and put down. Out of every one of these stages grading and sorting of fruits are vital way. The main end is to plan an automated system that improves the standard, upgrades the creation productivity, decreases the work cost of the fashion, and assesses the internal quality of the fruits. As per the agricultural and food products export development authority pomegranates, mangoes, bananas, papayas, and orange account for the larger portion of fruits exported from our country. Effective discovery is achieved using hyperspectral imaging, CNN frame. Superior performance than treating, sorting, and grading grounded on redundant classes in the CNN frame through the proposed architecture.
KW - CNN framework
KW - Hyperspectral Imaging (HSI)
KW - Internal quality
UR - https://www.scopus.com/pages/publications/85147844769
U2 - 10.1007/978-981-19-7169-3_5
DO - 10.1007/978-981-19-7169-3_5
M3 - Conference contribution
AN - SCOPUS:85147844769
SN - 9789811971686
T3 - Lecture Notes in Electrical Engineering
SP - 49
EP - 57
BT - Computer Vision and Machine Intelligence Paradigms for SDGs - Select Proceedings of ICRTAC-CVMIP 2021
A2 - Kannan, R. Jagadeesh
A2 - Thampi, Sabu M.
A2 - Wang, Shyh-Hau
PB - Springer Science and Business Media Deutschland GmbH
T2 - 4th International Conference on Recent Trends in Advanced Computing - Computer Vision and Machine Intelligence Paradigms for Sustainable Development Goals, ICRTAC-CVMIP 2021
Y2 - 11 November 2021 through 12 November 2021
ER -