AgroBrain: An Automated Crop Recommendation System Based on Soil Classification Using CNN And Ensemble Models

Kangana Mudiyanselage, Malmi

dc.contributor.author	Kangana Mudiyanselage, Malmi
dc.date.accessioned	2024-04-19T06:31:57Z
dc.date.available	2024-04-19T06:31:57Z
dc.date.issued	2023
dc.identifier.citation	Kangana Mudiyanselage, Malmi (2023) AgroBrain: An Automated Crop Recommendation System Based on Soil Classification Using CNN And Ensemble Models. BSc. Dissertation, Informatics Institute of Technology	en_US
dc.identifier.issn	20191224
dc.identifier.uri	http://dlib.iit.ac.lk/xmlui/handle/123456789/2013
dc.description.abstract	"Sri Lanka's spice industry plays a significant role in the country's economy, exporting over 30,000 tons of rare and expensive spices annually. However, the market has recently faced challenges due to harvest losses caused by a lack of knowledge about suitable crops for specific land plots.[1] This research paper focuses on addressing these issues by proposing the integration of new technologies in spice agriculture and aims to bridge the gap between traditional practices and technological advancements in spice agriculture, ultimately strengthening the sector and ensuring its sustainability."	en_US
dc.language.iso	en	en_US
dc.subject	Soil classification	en_US
dc.subject	Machine learning	en_US
dc.subject	Deep learning	en_US
dc.title	AgroBrain: An Automated Crop Recommendation System Based on Soil Classification Using CNN And Ensemble Models	en_US
dc.type	Thesis	en_US