2022
DOI: 10.30955/gnj.004560
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Deep Learning Driven Crop Classification and Chlorophyll Content Estimation for the Nexus Food higher Productions using Multi-spectral Remote Sensing Images

Abstract: <p>Due to the development of open access medium-high resolution remote sensing data like multispectral remote sensing images, crop classification becomes a hot research topic to be realized on large scale using machine learning (ML) models. At the same time, chlorophyll content is a critical index used for defining crop growth conditions, photosynthetic ability, and physiological position. It has an adaptive characteristic which finds useful to monitor crop growth conditions and understand the procedure … Show more

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Cited by 2 publications
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“…Lastly, a dolphin swarm optimizer (DSO) with a deep SDAE (DSDAE) algorithm was employed for classifying types of crops. Karthikeyan et al (2023) introduced a novel remora optimizer with a DL-driven crop classification and chlorophyll contents estimation (RODLD-C4E) approach that exploited multispectral RSIs. To achieve this, this developed RODLD-C4E algorithm primarily arises using an RO method with NASNetLarge framework to extract features.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Lastly, a dolphin swarm optimizer (DSO) with a deep SDAE (DSDAE) algorithm was employed for classifying types of crops. Karthikeyan et al (2023) introduced a novel remora optimizer with a DL-driven crop classification and chlorophyll contents estimation (RODLD-C4E) approach that exploited multispectral RSIs. To achieve this, this developed RODLD-C4E algorithm primarily arises using an RO method with NASNetLarge framework to extract features.…”
Section: Literature Reviewmentioning
confidence: 99%