#5904. A deep learning-based novel approach for weed growth estimation

August 2026publication date
Proposal available till 03-06-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Geometry and Topology;
Theoretical Computer Science;
Software;
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Abstract:
Automation of agricultural food production is growing in popularity in scientific communities and industry. The main goal of automation is to identify and detect weeds in the crop. Weed intervention for the duration of crop establishment is a serious difficulty for wheat in North India. The soil nutrient is important for crop production. Weeds usually compete for light, water and air of nutrients and space from the target crop. This research paper assesses the growth rate of weeds due to macronutrients (nitrogen, phosphorus and potassium) absorbed from various soils (fertile, clay and loamy) in the rabi crop field.
Keywords:
Deep learning; Efficient Net-B7; Inception V4; Rabi crop; Soil nutrients; Weed identification; Weeds

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