Light weight YOLOv8 for real-time sugarcane stem node detection, counting, and monitoring in complex natural environments
*Pushpendra KumarCorresponding authorpushpendra22csd010@ncuindia.eduDepartment of Computer Science and EngineeringThe Northcap UniversityGurugram, Haryana, 201206, IndiaView full profile → , Shraddha Arorashraddhaarora@ncuindia.eduDepartment of Computer Science and EngineeringThe Northcap UniversityGurugram, Haryana, 201206, IndiaView full profile → , Shaveta Arorashavetaaarora@ncuindia.eduDepartment of Computer Science and EngineeringThe Northcap UniversityGurugram, Haryana, 201206, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 12 Nov 2024
- Published Online:
- 17 Mar 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1915
- Pages:
- 305–315
Abstract
Keywords
Subject Classifications
References
[1] Moises Alencastre-Miranda, Rodrigo S. Souza, Fábio S. Araújo, Felipe A. Araujo, and Sergio R. P. Silva, “Convolutional Neural Networks and Transfer Learning for Quality Inspection of Different Sugarcane Varieties,” IEEE Transactions on Industrial Informatics, vol. 17, no. 2, pp. 787–94 (2020).
[2] Angel Pontin Garcia, Gabriel D. Y. S. de Almeida, Augusto C. de Oliveira, and José P. R. de Oliveira, “Sensor-Based Technologies in Sugarcane Agriculture,” Sugar Tech, vol. 24, no. 3, pp. 679–98 (2022).
[3] Rupali Mangrule and Khan Rahat Afreen, “Automated Sugarcane Crop Disease Forecasting with Colour and Texture Features,” Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, pp. 1–15 (2023).
[4] João Batista Ribeiro, Sergio M. de Oliveira, Douglas L. Sequeira, Marcos A. de Lima, and Paulo C. F. de Lima, “Automated Detection of Sugarcane Crop Lines from UAV Images Using Deep Learning,” Information Processing in Agriculture (2023).
[5] Guilherme de Moura Araújo, André F. Silva, Paulo C. F. de Lima, and João B. Ribeiro, “Sugarcane Harvesting Quality by Digital Image Processing,” Sugar Tech, vol. 23, pp. 209–18 (2021).
[6] Haofeng Deng, Jie Li, Zhiwei Jiang, and Cheng Chen, “OpenCV Based Detection and Recognition System of Pre-Seed Cutting Sugarcane Planter,” Second International Symposium on Computer Technology and Information Science (ISCTIS 2022), vol. 12474, pp. 192–96 (2022).
[7] Yukti Gupta, P. A. S. S. R. Kumar, and A. K. S. Pandey, “Micropropagation: A Biotechnological Tool for Rapid Seed Multiplication in Sugarcane,” (2020).
[8] Da Wang, Xin Zhang, Zhiwei Jiang, and Y. Xie, “Sugarcane-Seed-Cutting System Based on Machine Vision in Pre-Seed Mode,” Sensors, vol. 22, no. 21, p. 8430 (2022).
[9] Deqiang Zhou, Yunlei Fan, Zhiyong Chen, and Yao Liu, “A New Design of Sugarcane Seed Cutting Systems Based on Machine Vision,” Computers and Electronics in Agriculture, vol. 175, p. 105611 (2020).
[10] Wen Chen, Liqiang Liu, and Zhenhua Zhang, “Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion,” Applied Sciences, vol. 11, no. 18, p. 8663 (2021).
[11] Deqiang Zhou, Wenbo Zhao, Yunlei Fan, and Zhiyong Chen, “Identification and Localisation Algorithm for Sugarcane Stem Nodes by Combining YOLOv3 and Traditional Methods of Computer Vision,” Sensors, vol. 22, no. 21, p. 8266 (2022).
[12] Chunming Wen, Shaohui Zhang, and Xiaoyu Zhang, “Sugarcane Node Detection Method Based on Photoelectric Sensor Vertical Projection Signal Processing,” (2023).
[13] Hongzhen Xu, Guoqing Tan, Weifeng Yang, and Tao Liu, “Feature Extraction and Identification of Sugarcane Bud Based on S Component in HSV Model,” Recent Advances in Electrical & Electronic Engineering, vol. 16, no. 1, pp. 78–89 (2023).
[14] Kang Yu, Yunlei Fan, Deqiang Zhou, and Zhiyong Chen, “MobileNet-YOLO V5s: An Improved Lightweight Method for Real-Time Detection of Sugarcane Stem Nodes in Complex Natural Environments,” IEEE Access (2023).
[15] Phillip Chlap, René L. Almeida, and Alex K. Song, “A Review of Medical Image Data Augmentation Techniques for Deep Learning Applications,” Journal of Medical Imaging and Radiation Oncology, vol. 65, no. 5, pp. 545–63 (2021).
[16] Glenn Jocher, Jonathan Qiu, and Aayush Chaurasia, “Ultralytics YOLO,” (2023).
[17] Zhi Tian, Weijun Shen, and Hongyu Chen, “FCOS: A Simple and Strong Anchor-Free Object Detector,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 4, pp. 1922–33 (2020).
[18] Garima Saini, Arun Kumar Yadav, and Rajeev Choudhary, “Structural equation-based model to investigate the moderating effect of fear of COVID using partial least square method,” Journal of Interdisciplinary Mathematics, vol. 25, no. 3, pp. 703–720 (2022).
[19] Mukesh Kumar Gupta, Priya Sharma, and Anupama Saxena, “Detection and Localization for Watermarking Technique Using LSB Encryption for DICOM Image,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 25, no. 1, pp. 193–204 (2022).




