Abstract
It is essential to identify the weed growth in plant infection at an earlier stage, which is an important procedure of precision agriculture. In this research paper, we found that the optimum methods by positioning appropriate optical sensors to acquire the most relevant images to interpret the plant, identification of weed infections in the plant bed, and accurate identification of intrusion through the images. We introduced a variant of singular value decomposition for this purpose to achieve the best possible results. The performance of this modified singular value decomposition by our work is found better than the conventional singular value decomposition-based feature extraction. Comparison of aerial and portrait images was done to identify the best choice according to the required identification.
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Ramesh, K., Samraj, A. (2021). Simplified SVD Feature Construction in Multiangle Images to Identify Plant Varieties and Weed Infestation. In: Chiplunkar, N.N., Fukao, T. (eds) Advances in Artificial Intelligence and Data Engineering. AIDE 2019. Advances in Intelligent Systems and Computing, vol 1133. Springer, Singapore. https://doi.org/10.1007/978-981-15-3514-7_85
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DOI: https://doi.org/10.1007/978-981-15-3514-7_85
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