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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
Publication Fee: 599/- INR
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 05

Published on: May 2026

SPATIO-TEMPORAL MODELLING FOR MULTI-STAGE RADISH QUALITY MONITORING:A COMPARATIVE STUDY OF CNN AND CNN-LSTM ARCHITECTURES

Teesha Sinha

Dr. V. Arun

Department of Computing Technologies ,SRM Institute of Science and Technology, Kattankulathur, India-603203
DOI:https://doi.org/10.55041/ijcope.v2i5.124

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Abstract

For The degradation of vegetable quality begins during the growth stage and continues through various stages before harvest. Most of the existing computer vision-based methods are limited to single-stage or post-harvest vegetable quality assessment, without considering the temporal aspect. In this paper, a spatio-temporal approach for multi-stage vegetable quality assessment using proximal images is presented. A convolutional neural network (CNN) is employed for spatial feature extraction, and a CNN-LSTM hybrid model is developed to capture the temporal quality dynamics during specified growth stages. A comparative study of CNN and CNN-LSTM models is performed on modified public datasets with artificially generated stage-wise sequences. The experimental findings show that incorporating temporal information improves quality prediction accuracy, F1- score, and temporal consistency.

How to Cite this Paper

Sinha, T. (2026). Spatio-Temporal Modelling for Multi-Stage Radish Quality Monitoring:A Comparative Study of CNN and CNN-LSTM Architectures. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.124

Sinha, Teesha. "Spatio-Temporal Modelling for Multi-Stage Radish Quality Monitoring:A Comparative Study of CNN and CNN-LSTM Architectures." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.124.

Sinha, Teesha. "Spatio-Temporal Modelling for Multi-Stage Radish Quality Monitoring:A Comparative Study of CNN and CNN-LSTM Architectures." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.124.

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References


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  • •Published on: May 06 2026
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